期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到499,870篇文章
< 1 2 … 250 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
A Metaheuristic Football Optimization Algorithm Integrated with Large Language Models for Automated Seismic Time-Series Modeling 认领 引用
1
作者 Amal H.Alharbi Marwa M.Eid +2 位作者 Nima Khodadadi Ebrahim A.Mattar Sayed Elkenawy 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第5期947-987,共41页
Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Alt... Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Although recent studies have improved neural architectures and optimization techniques,preprocessing is often treated as a fixed or manually designed stage,with limited integration into model optimization.To address this,this paper proposes an integrated,data-driven modelling framework that combines guided preprocessing with systematic hyperparameter optimization for seismic prediction,specifically forecasting earthquake magnitude from seismic catalog time-series data,with experiments conducted on Canadian seismic records.The method uses a Large Language Model to guide data preparation and feature engineering,rather than fully automate them,and applies deep learning-based forecasting with the N-HITS architecture,optimized via metaheuristic-assisted feature selection and hyperparameter tuning.The Football Optimization Algorithm(FbOA),employed as a metaheuristic optimization strategy in this study,is evaluated and compared with several well-known optimizers under identical conditions.The results show significant performance gains,with FbOA achieving superior accuracy,robustness,and convergence compared to baseline and competing methods.Notably,error metrics are reduced(MSE 3.10×10-7,RMSE 5.57×103),with high performance indicators(r=0.982,R2=0.979,NSE=0.981,WI=0.985).These results highlight the value of integrating guided preprocessing with optimization and demonstrate a scalable framework for high-precision time-series prediction in geophysical and related domains. 展开更多
关键词 Seismic time-series forecasting large language models metaheuristic algorithms football optimization algorithm earthquake modeling
暂未订购 下载PDF
Research on a two-step retracking algorithm for reconstructed waveforms of nearshore radar altimeters 认领 引用
2
作者 Yongjun Jia Xingwei Jiang +1 位作者 Dan Qin Bo Yuan 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2026年第3期216-231,共16页
To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decompositio... To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decomposition(EMD)to extract trend information from the trailing edge of the waveform.Reconstructed waveforms are formed by linking the leading and trailing edge trend information.The retracking process consists of two steps:the first step focuses on retracking a segment of the leading edge to obtain 4 crucial a priori parameters.In the second step,retracking incorporates both the leading and trailing edges using the previously acquired a priori information.We tested the algorithm using data from the HY-2B radar altimeter.Results indicate that the proposed two-step retracking algorithm outperforms the Maximum Likelihood Estimation(MLE4)algorithm currently used in the operational processing of the HY-2B radar altimeter,as well as the Adaptive Leading Edge Subwaveform(ALES)algorithm,in terms of significant wave height(SWH)and sea level anomalies(SLA).Specifically,the standard deviation of the difference in SWH is reduced by 14%,and the standard deviation of the difference in SLA is reduced by approximately 18%.The two-step retracking algorithm effectively leverages trailing edge information,reduces the influence of peak noise on the leading edge,and improves both the utilization and accuracy of the waveform retracking. 展开更多
关键词 reconstructed waveforms two-step retracking algorithm radar altimeter HY-2B satellite
暂未订购 下载PDF
Prediction model for indoor rock compression failure time based on ensemble learning and optimization algorithms 认领 引用 被引量：1
3
作者 Boyang Zhang Xiancheng Wang +5 位作者 Fei Ding Liyuan Yu Luyuan Wu Shuai Zhao Yingkang Weng Zhaoyang Feng 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2026年第7期2437-2453,共17页
The prediction of rock failure,a key fundamental research for addressing mining safety issues(such as mine slope stability and rockburst),faces challenges with traditional methods due to their complex generalization a... The prediction of rock failure,a key fundamental research for addressing mining safety issues(such as mine slope stability and rockburst),faces challenges with traditional methods due to their complex generalization and computational processes that struggle to describe the entire failure process.Consequently,12 prediction models integrating ensemble learning and optimization algorithms were established to predict rock peak stress and failure time using strain,elastic modulus,density,mass,and confining pressure as inputs.Fivefold cross-validation was used to optimize hyperparameters,significantly improving the model's generalization ability,robustness,and stability.Dataset was established through rock mechanics experiments,with strain increments configured at 0.008‰,0.01‰,and 0.012‰ in the test set.The cross-validation optimized particle swarm optimization eXtreme gradient boosting(CV-PSO-XGBoost)model performed best under a strain increment of 0.01‰,and its stress prediction achieved coefficient of determination R2=0.904,mean absolute error(MAE)=4.315,and root mean square error(RMSE)=5.435;while the failure time prediction demonstrated R2=0.811,mean absolute percentage error(MAPE)=7.842%,and MAE=30.343.Finally,SHapley Additive explanations(SHAP)analysis showed strain and stress significantly impact the model,with strain positively predicting failure time,aligning with traditional rock validating reliability.This study provides insights into the research on rock strata stability in mining. 展开更多
关键词 rock failure strain increment failure time ensemble learning SHapley Additive exPlanations interpretation
暂未订购 下载PDF
Improved simulated annealing algorithm for UAV path planning with uncertain flight time 认领 引用
4
作者 LI Xiaoduo LUO He +1 位作者 WANG Guoqiang YIN Youlong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第1期272-286,共15页
Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always ... Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit. 展开更多
关键词 unmanned aerial vehicle(UAV)path planning uncertain flight time robust optimization simulated annealing
暂未订购 下载PDF
Ocean bottom seismograph relocation and time correction using the MCMC algorithm 认领 引用 被引量：1
5
作者 Hao Hu Xiongwei Niu +6 位作者 Wei Wang Wencai Xu Aiguo Ruan Wenfei Gong Xiaodong Wei Mingju Xu Tao Li 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2025年第10期101-111,共11页
The ocean bottom seismograph(OBS)is a powerful device deployed on the seafloor for acquiring marine seismic data,capable of detecting the multi-scale Earth’s interiors from submarine sediments to the mantle.Due to th... The ocean bottom seismograph(OBS)is a powerful device deployed on the seafloor for acquiring marine seismic data,capable of detecting the multi-scale Earth’s interiors from submarine sediments to the mantle.Due to the frequent use of free-fall deployment,it is challenging to accurately track its precise position.Additionally,the internal crystal oscillator clock of the OBS has limited accuracy,resulting in clock drift for long-term work on the seabed.To improve the reliability of OBS detections,it is crucial to calculate the precise OBS location and time correction.Focusing on accurately determining OBS position and timing,this study developed a positioning method that integrates time correction based on the Markov Chain Monte Carlo(MCMC)algorithm,utilizing travel times of direct water waves triggered by two-dimensional(2-D)shot lines or three-dimensional(3-D)airgun arrays.This newly developed method can simultaneously estimate accurate OBS location and time correction,incorporating bathymetric data into the inversion procedures to improve sampling efficiency and enhance the reliability of the final results.Synthetic tests with appropriate noise levels are performed independently to evaluate the feasibility and reliability of our method,indicating that it is robust enough to determine OBS location and time correction precisely.Finally,we use travel-time data recorded at three OBSs deployed in the Southwest Indian Ridge to relocate locations and calculate time corrections.The results exhibit high consistency when using 2-D and 3-D shot data,indicating that high-resolution bathymetric data plays a fingerprint role in inversion to evaluate precise OBS location and time correction. 展开更多
关键词 ocean bottom seismograph positioning time correction marine seismic data acquisition Metropolis-Hastings algorithm marine seismic observation
暂未订购 下载PDF
Anytime algorithm based on adaptive variable-step-size mechanism for path planning of UAVs 认领 引用 被引量：2
6
作者 Hui GAO Yuhong JIA +3 位作者 Liwen XU Fengxing PAN Shaowei LI Yaoming ZHOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第9期283-303,共21页
For autonomous Unmanned Aerial Vehicles(UAVs)flying in real-world scenarios,time for path planning is always limited,which is a challenge known as the anytime problem.Anytime planners address this by finding a collisi... For autonomous Unmanned Aerial Vehicles(UAVs)flying in real-world scenarios,time for path planning is always limited,which is a challenge known as the anytime problem.Anytime planners address this by finding a collision-free path quickly and then improving it until time runs out,making UAVs more adaptable to different mission scenarios.However,current anytime algorithms based on A*have insufficient control over the suboptimality bounds of paths and tend to lose their anytime properties in environments with large concave obstacles.This paper proposes a novel anytime path planning algorithm,Anytime Radiation A*(ARa A*),which can generate a series of suboptimal paths with improved bounds through decreasing search step sizes and can generate the optimal path when time is sufficient.The ARa A*features two main innovations:an adaptive variable-step-size mechanism and elliptic constraints based on waypoints.The former helps achieve fast path searching in various environments.The latter allows ARa A*to control the suboptimality bounds of paths and further enhance search efficiency.Simulation experiments show that the ARa A*outperforms Anytime Repairing A*(ARA*)and Anytime D*(AD*)in controlling suboptimality bounds and planning time,especially in environments with large concave obstacles.Final flight experiments demonstrate that the paths planned by ARa A*can ensure the safe flight of quadrotors. 展开更多
关键词 Path planning Anytime algorithm Adaptive variable-step-size Suboptimality bound Unmanned aerial vehicle(UAV)
暂未订购 下载PDF
Adaptive Time Synchronization in Time Sensitive-Wireless Sensor Networks Based on Stochastic Gradient Algorithms Framework 认领 引用 被引量：2
7
作者 Ramadan Abdul-Rashid Mohd Amiruddin Abd Rahman +1 位作者 Kar Tim Chan Arun Kumar Sangaiah 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第3期2585-2616,共32页
This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different... This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications. 展开更多
关键词 Wireless sensor network time synchronization stochastic gradient algorithm multi-hop
暂未订购 下载PDF
Real-Time Programmable Nonlinear Wavefront Shaping with Si Metasurface Driven by Genetic Algorithm 认领 引用 被引量：1
8
作者 Ze Zheng Gabriel Sanderson +4 位作者 Soheil Sotoodeh Chris Clifton Cuifeng Ying Mohsen Rahmani Lei Xu 《Engineering》 SCIE EI CSCD 2025年第6期90-95,共6页
Nonlinear wavefront shaping is crucial for advancing optical technologies,enabling applications in optical computation,information processing,and imaging.However,a significant challenge is that once a metasurface is f... Nonlinear wavefront shaping is crucial for advancing optical technologies,enabling applications in optical computation,information processing,and imaging.However,a significant challenge is that once a metasurface is fabricated,the nonlinear wavefront it generates is fixed,offering little flexibility.This limitation often necessitates the fabrication of different metasurfaces for different wavefronts,which is both time-consuming and inefficient.To address this,we combine evolutionary algorithms with spatial light modulators(SLMs)to dynamically control wavefronts using a single metasurface,reducing the need for multiple fabrications and enabling the generation of arbitrary nonlinear wavefront patterns without requiring complicated optical alignment.We demonstrate this approach by introducing a genetic algorithm(GA)to manipulate visible wavefronts converted from near-infrared light via third-harmonic generation(THG)in a silicon metasurface.The Si metasurface supports multipolar Mie resonances that strongly enhance light-matter interactions,thereby significantly boosting THG emission at resonant positions.Additionally,the cubic relationship between THG emission and the infrared input reduces noise in the diffractive patterns produced by the SLM.This allows for precise experimental engineering of the nonlinear emission patterns with fewer alignment constraints.Our approach paves the way for self-optimized nonlinear wavefront shaping,advancing optical computation and information processing techniques. 展开更多
关键词 Nonlinear metasurface Genetic algorithm Wavefront manipulation
暂未订购 下载PDF
A Wearable Stethoscope for Accurate Real-Time Lung Sound Monitoring and Automatic Wheezing Detection Based on an AI Algorithm 认领 引用
9
作者 Kyoung-Ryul Lee Taewi Kim +12 位作者 Sunghoon Im Yi Jae Lee Seongeun Jeong Hanho Shin Hana Cho Sang-Heon Park Minho Kim Jin Goo Lee Dohyeong Kim Gil-Soon Choi Daeshik Kang SungChul Seo Soo Hyun Lee 《Engineering》 SCIE EI CSCD 2025年第10期116-129,共14页
The various bioacoustics signals obtained with auscultation contain complex clinical information that has been traditionally used as biomarkers,however,they are not extensively used in clinical studies owing to their ... The various bioacoustics signals obtained with auscultation contain complex clinical information that has been traditionally used as biomarkers,however,they are not extensively used in clinical studies owing to their spatiotemporal limitations.In this study,we developed a wearable stethoscope for wireless,skinattachable,low-power,continuous,real-time auscultation using a lung-sound-monitoring-patch(LSMP).LSMP can monitor respiratory function through a mobile app and classify normal and adventitious breathing by comparing their unique acoustic characteristics.The human heart and breathing sounds from humans can be distinguished from complex sound signals consisting of a mixture of bioacoustic signals and external noise.The performance of the LSMP sensor was further demonstrated in pediatric patients with asthma and elderly chronic obstructive pulmonary disease(COPD)patients where wheezing sounds were classified at specific frequencies.In addition,we developed a novel method for counting wheezing events based on a two-dimensional convolutional neural network deep-learning model constructed de novo and trained with our augmented fundamental lung-sound data set.We implemented a counting algorithm to identify wheezing events in real-time regardless of the respiratory cycle.The artificial intelligence-based adventitious breathing event counter distinguished>80%of the events(especially wheezing)in long-term clinical applications in patients with COPD. 展开更多
关键词 Wearable stethoscope Lung sound Real-time monitoring Automatic wheeze detection AI algorithm
暂未订购 下载PDF
Distributed Robust Predefined-Time Algorithm for Seeking Nash Equilibrium in MASs 认领 引用 被引量：1
10
作者 Jing-Zhe Xu Zhi-Wei Liu +2 位作者 Ming-Feng Ge Yan-Wu Wang Dingxin He 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第5期1053-1055,共3页
Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communicatio... Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communication.To this end,a novel distributed robust predefined-time algorithm is proposed,which ensures the precise convergence of agent states to the NE within a settling time that can be directly determined by adjusting one or more parameters.The proposed algorithm employs an integral sliding mode strategy to effectively reject disturbances.Additionally,a consensus-based estimator is designed to overcome the challenge of limited information availability,where each agent can only access information from its directly connected neighbors,which conflicts with the computation of the cost function that requires information from all agents.Finally,a numerical example is provided to demonstrate the algorithm's effectiveness and performance. 展开更多
关键词 seeking nash convergence agent states multi agent systems integral sliding mode strateg non cooperative games Nash equilibrium distributed algorithm robust control
暂未订购 下载PDF
An Efficient Clustering Algorithm for Enhancing the Lifetime and Energy Efficiency of Wireless Sensor Networks 认领 引用
11
作者 Peng Zhou Wei Chen Bingyu Cao 《Computers, Materials & Continua》 SCIE EI 2025年第9期5337-5360,共24页
Wireless Sensor Networks(WSNs),as a crucial component of the Internet of Things(IoT),are widely used in environmental monitoring,industrial control,and security surveillance.However,WSNs still face challenges such as ... Wireless Sensor Networks(WSNs),as a crucial component of the Internet of Things(IoT),are widely used in environmental monitoring,industrial control,and security surveillance.However,WSNs still face challenges such as inaccurate node clustering,low energy efficiency,and shortened network lifespan in practical deployments,which significantly limit their large-scale application.To address these issues,this paper proposes an Adaptive Chaotic Ant Colony Optimization algorithm(AC-ACO),aiming to optimize the energy utilization and system lifespan of WSNs.AC-ACO combines the path-planning capability of Ant Colony Optimization(ACO)with the dynamic characteristics of chaotic mapping and introduces an adaptive mechanism to enhance the algorithm’s flexibility and adaptability.By dynamically adjusting the pheromone evaporation factor and heuristic weights,efficient node clustering is achieved.Additionally,a chaotic mapping initialization strategy is employed to enhance population diversity and avoid premature convergence.To validate the algorithm’s performance,this paper compares AC-ACO with clustering methods such as Low-Energy Adaptive Clustering Hierarchy(LEACH),ACO,Particle Swarm Optimization(PSO),and Genetic Algorithm(GA).Simulation results demonstrate that AC-ACO outperforms the compared algorithms in key metrics such as energy consumption optimization,network lifetime extension,and communication delay reduction,providing an efficient solution for improving energy efficiency and ensuring long-term stable operation of wireless sensor networks. 展开更多
关键词 Internet of Things wireless sensor networks ant colony optimization clustering algorithm energy efficiency
暂未订购 下载PDF
Probabilistic Assessment of PV-DG for Optimal Multi-Locations and Sizing Using Genetic Algorithm and Sequential-Time Power Flow 认领 引用
12
作者 A. Elkholy 《Journal of Power and Energy Engineering》 2025年第2期23-42,共20页
This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal ... This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results. 展开更多
关键词 Photovoltaic Distributed Generation Probability Genetic Algorithm Radial Distribution Systems Time Series Power Flow
暂未订购 下载PDF
Phase matching sampling algorithm for sampling rate reduction in time division multiplexing optical fiber sensor system 认领 引用
13
作者 Junhui Wu Zhilin Xu +2 位作者 Yi Shi Yurong Liang Qizhen Sun 《Opto-Electronic Technology》 2025年第2期51-63,共13页
Time division multiplexing(TDM)architecture is an important approach to creating sensor arrays for massive scale monitoring.But it is paradoxical for the TDM interferometric sensor array to keep a short delay fiber fo... Time division multiplexing(TDM)architecture is an important approach to creating sensor arrays for massive scale monitoring.But it is paradoxical for the TDM interferometric sensor array to keep a short delay fiber for high sensing resolution and meanwhile use low sampling rate for practical applications.In this paper,a phase matching sampling(PMS)paradigm is proposed to address the above contradiction.By matching the phase of the sampling clock with the delay fiber length,combining with multiple-pulses sampling strategy,the proposed PMS method can avoid collecting the redundant information,facilitating the decreasing of sampling rate as well as delay fiber length of the TDM sensing system.The proof-of-concept experiments on an 8-channel TDM interferometric system demonstrate that when the sampling rate is fixed at 20 MS/s,by applying the PMS algorithm,the delay fiber length can be shortened from 100 m to 1 m,compared with applying the conventional sampling method.It reduced the phase noise of the system by a factor of 10 at 1 mHz and by a factor of 50 at 1 Hz.The PMS algorithm for greatly reducing the sampling rate is expected to fuel the TDM interferometric sensor arrays for many applications. 展开更多
关键词 time division multiplexing system sampling algorithm interferometric fiber optic sensors displacement sensing array
暂未订购 下载PDF
Solving open vehicle problem with time window by hybrid column generation algorithm 认领 引用 被引量：1
14
作者 YU Naikang QIAN Bin +2 位作者 HU Rong CHEN Yuwang WANG Ling 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2022年第4期997-1009,共13页
This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the ... This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time. 展开更多
关键词 open vehicle routing problem with time window(OVRPTW) hybrid column generation algorithm(HCGA) mixed integer programming label setting algorithm
暂未订购 下载PDF
Algorithm for computing time correlation functions in non-stationary complex dynamic systems 认领 引用
15
作者 Jiu Zhang Lifu Jin +4 位作者 Bo Zheng Xiongfei Jiang Tingting Chen Cong Xu Yanqing Hu 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第3期77-83,共7页
For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The propose... For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The proposed algorithm integrates two-point and multi-point time correlation functions into a unified framework.Further,it is verified by a practical application in complex financial systems,demonstrating its potential in various complex dynamic systems. 展开更多
关键词 complex dynamic systems non-stationary states time correlation functions
暂未订购 下载PDF
A new escape time algorithm of constructing Julia set 认领 引用
16
作者 袁杰 Li Xiali +1 位作者 Hou Zhiling Cao Maosheng 《High Technology Letters》 EI CAS 2007年第2期194-197,共4页
Escape time algorithm is an effective theoretical algorithm of constructing fractal graphics. The key of this algorithm lies in the construction of escape time function. A new escape time function is presented based o... Escape time algorithm is an effective theoretical algorithm of constructing fractal graphics. The key of this algorithm lies in the construction of escape time function. A new escape time function is presented based on the research of escape time algorithm. An accelerated escape time algorithm is carried out in this paper. The experiments have demonstrated that the new algorithm is not only as precise as the old, but also faster when it is used to construct Julia set. 展开更多
关键词 fractal escape time algorithm escape time function Julia set
暂未订购 下载PDF
TRLLD:Load Level Detection Algorithm Based on Threshold Recognition for Load Time Series 认领 引用
17
作者 Qingqing Song Shaoliang Xia Zhen Wu 《Computers, Materials & Continua》 SCIE EI 2025年第5期2619-2642,共24页
Load time series analysis is critical for resource management and optimization decisions,especially automated analysis techniques.Existing research has insufficiently interpreted the overall characteristics of samples... Load time series analysis is critical for resource management and optimization decisions,especially automated analysis techniques.Existing research has insufficiently interpreted the overall characteristics of samples,leading to significant differences in load level detection conclusions for samples with different characteristics(trend,seasonality,cyclicality).Achieving automated,feature-adaptive,and quantifiable analysis methods remains a challenge.This paper proposes a Threshold Recognition-based Load Level Detection Algorithm(TRLLD),which effectively identifies different load level regions in samples of arbitrary size and distribution type based on sample characteristics.By utilizing distribution density uniformity,the algorithm classifies data points and ultimately obtains normalized load values.In the feature recognition step,the algorithm employs the Density Uniformity Index Based on Differences(DUID),High Load Level Concentration(HLLC),and Low Load Level Concentration(LLLC)to assess sample characteristics,which are independent of specific load values,providing a standardized perspective on features,ensuring high efficiency and strong interpretability.Compared to traditional methods,the proposed approach demonstrates better adaptive and real-time analysis capabilities.Experimental results indicate that it can effectively identify high load and low load regions in 16 groups of time series samples with different load characteristics,yielding highly interpretable results.The correlation between the DUID and sample density distribution uniformity reaches 98.08%.When introducing 10% MAD intensity noise,the maximum relative error is 4.72%,showcasing high robustness.Notably,it exhibits significant advantages in general and low sample scenarios. 展开更多
关键词 Load time series load level detection threshold recognition density uniformity index outlier detection management systems engineering
暂未订购 下载PDF
LOA-RPL:Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime 认领 引用
18
作者 Sankar Sennan Somula Ramasubbareddy +2 位作者 Anand Nayyar Yunyoung Nam Mohamed Abouhawwash 《Computers, Materials & Continua》 SCIE EI 2021年第10期351-371,共21页
Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a c... Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a network.However,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH node.Consequently,early battery depletion is produced near the sink.To overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this study.LOA-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean distance.CH selection is performed using LOA.Route establishment is implemented using residual energy information.An extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and throughput.The performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and throughput.The proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and RISA-RPL.LOA-RPL is also highly energy-efficient compared with other similar routing protocols. 展开更多
关键词 Internet of things cluster head clustering protocol optimization algorithm lion optimization algorithm network lifetime routing protocol wireless sensor networks energy consumption low-power and lossy networks
暂未订购 下载PDF
Wind power time series simulation model based on typical daily output processes and Markov algorithm 认领 引用 被引量：4
19
作者 Zhihui Cong Yuecong Yu +1 位作者 Linyan Li Jie Yan 《Global Energy Interconnection》 EI CSCD 2022年第1期44-54,共11页
The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind powe... The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves. 展开更多
关键词 Wind power Time series Typical daily output processes Markov algorithm Modified K-means clustering algorithm
暂未订购 下载PDF
Enhanced Sentiment Analysis Algorithms for Multi-Weight Polarity Selection on Twitter Dataset 认领 引用
20
作者 Ayman Mohamed Mostafa 《Intelligent Automation & Soft Computing》 SCIE 2023年第1期1015-1034,共20页
Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects.Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy.T... Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects.Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy.The sentiment analysis accuracy depends mainly on supervised and unsupervised mechanisms.Supervised mechanisms are based on machine learning algorithms that achieve moderate or high accuracy but the manual annotation of data is considered a time-consuming process.In unsupervised mechanisms,a lexicon is constructed for storing polarity terms.The accuracy of analyzing data is considered moderate or low if the lexicon contains small terms.In addition,most research methodologies analyze datasets using only 3-weight polarity that can mainly affect the performance of the analysis process.Applying both methods for obtaining high accuracy and efficiency with low user intervention during the analysis process is considered a challenging process.This paper provides a comprehensive evaluation of polarity weights and mechanisms for recent sentiment analysis research.A semi-supervised framework is applied for processing data using both lexicon and machine learning algorithms.An interactive sentiment analysis algorithm is proposed for distributing multi-weight polarities on Arabic lexicons that contain high morphological and linguistic terms.An enhanced scaling algorithm is embedded in the multi-weight algorithm to assign recommended weight polarities automatically.The experimental results are conducted on two datasets to measure the over-all accuracy of proposed algorithms that achieved high results when compared to machine learning algorithms. 展开更多
关键词 Sentiment analysis semi-supervised framework multi-weight polarity algorithm Arabic lexicons and automated scaling algorithm
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈