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Randomized Algorithms for Probabilistic Optimal Robust Performance Controller Design 认领 引用 被引量：1
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作者 宋春雷 谢玲 《Journal of Beijing Institute of Technology》 EI CAS 2004年第1期15-19,共5页
Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach wa... Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example. 展开更多
关键词 randomized algorithms statistical learning theory uniform convergence of empirical means (UCEM) probabilistic optimal robust performance controller design
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Randomized Algorithms for Computing the Generalized Tensor SVD Based on the Tensor Product 认领 引用
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作者 Salman Ahmadi-Asl Naeim Rezaeian Ugochukwu O.Ugwu 《Communications on Applied Mathematics and Computation》 EI CSCD 2026年第2期605-621,共17页
This work deals with developing two fast randomized algorithms for computing the generalized tensor singular value decomposition(GTSVD)based on the tensor product(T-product).The random projection method is utilized to... This work deals with developing two fast randomized algorithms for computing the generalized tensor singular value decomposition(GTSVD)based on the tensor product(T-product).The random projection method is utilized to compute the important actions of the underlying data tensors and use them to get small sketches of the original data tensors,which are easier to handle.Due to the small size of the tensor sketches,deterministic approaches are applied to them to compute their GTSVD.Then,from the GTSVD of the small tensor sketches,the GTSVD of the original large-scale data tensors is recovered.Some experiments are conducted to show the effectiveness of the proposed approach. 展开更多
关键词 Randomized algorithms Generalized tensor singular value decomposition(GTSVD) Tensor product(T-product)
Structured Random Cycle-Guided Algorithm (SRCA): An Adaptive Metaheuristic Combining Directionally-Guided and Stochastic Search Strategies 认领 引用
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作者 Giuseppe Marannano Antonino Cirello Tommaso Ingrassia 《Computers, Materials & Continua》 SCIE EI 2026年第6期1873-1898,共26页
In response to the growing need for adaptive optimization algorithms capable of handling complex,multimodal,and high-dimensional search spaces,this paper introduces the Structured Random Cycle-guided Algorithm(SRCA).S... In response to the growing need for adaptive optimization algorithms capable of handling complex,multimodal,and high-dimensional search spaces,this paper introduces the Structured Random Cycle-guided Algorithm(SRCA).SRCA is not presented as a fundamentally new optimization paradigm,but rather as an architectural synthesis and a unified adaptive framework for dynamic operator selection.Based on a cycle-structured architecture,directional and stochastic search behaviors are dynamically selected at the individual level.The algorithm orchestrates well-established structured movements with a diverse pool of stochastic exploration strategies,enabling a coherent and adaptive balance between exploration and exploitation throughout the optimization process.Unlike traditional metaheuristics that rely on fixed behavioral roles or static movement schemes,SRCA allows each individual to adapt its search strategy based on real-time population feedback,monitored through convergence and dispersion indicators.The performance of SRCA is quantitatively assessed under strictly identical experimental conditions on a comprehensive set of 23 benchmark functions,including multimodal and high-dimensional problems,as well as on six classical constrained engineering design problems.Numerical results demonstrate competitive convergence reliability and robustness across diverse optimization tasks,confirming the effectiveness of the proposed adaptive cycle-based framework. 展开更多
关键词 Metaheuristic algorithms optimization constrained optimization benchmark functions structured random cycle-guided algorithm
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Enhanced diagnosis of diabetic retinopathy:integrating advanced algorithms for automated detection and classification 认领 引用
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作者 E Murali T Prasad +2 位作者 JHari Krishna Abdul Hussain Sharief Peta Nandini 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2026年第4期637-645,共9页
AIM:To develop an automated diagnostic system for early detection of diabetic retinopathy(DR)using fundus images by identifying exudates,hemorrhages,and microaneurysms with advanced image processing and machine learni... AIM:To develop an automated diagnostic system for early detection of diabetic retinopathy(DR)using fundus images by identifying exudates,hemorrhages,and microaneurysms with advanced image processing and machine learning techniques.METHODS:Fundus images from the IDRiD dataset and additional Kaggle datasets were used.A wavelet-based band-pass filter was applied for edge enhancement of retinal features.Gaussian mixture model(GMM)clustering was used to segment and extract texture features.These extracted features were classified using machine learning algorithms,including a random forest classifier and a multilayer perceptron neural network.Performance metrics such as sensitivity,specificity,and accuracy were computed to evaluate the proposed model’s diagnostic effectiveness.RESULTS:The random forest-based classification system achieved a sensitivity of 95.08%,specificity of 86.67%,and overall accuracy of 95.20%in detecting DR lesions.The combination of wavelet-based edge enhancement,GMM clustering,and neural network-based feature classification demonstrated high reliability in lesion identification.CONCLUSION:The proposed method effectively detects early signs of DR from fundus images,offering a highaccuracy,automated,and scalable solution for assisting ophthalmologists.Its application can support large-scale screening programs,particularly in regions with limited access to specialized eye care. 展开更多
关键词 diabetic retinopathy random forest algorithm Gaussian mixture modelclustering multilayer perceptron fundus image analysis
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Randomized scheduling algorithm for input-queued switches 认领 引用 被引量：2
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作者 吴俊 罗军舟 《Journal of Southeast University(English Edition)》 EI CAS 2005年第1期6-10,共5页
The sampling problem for input-queued (IQ) randomized scheduling algorithms is analyzed.We observe that if the current scheduling decision is a maximum weighted matching (MWM),the MWM for the next slot mostly falls in... The sampling problem for input-queued (IQ) randomized scheduling algorithms is analyzed.We observe that if the current scheduling decision is a maximum weighted matching (MWM),the MWM for the next slot mostly falls in those matchings whose weight is closed to the current MWM.Using this heuristic,a novel randomized algorithm for IQ scheduling,named genetic algorithm-like scheduling algorithm (GALSA),is proposed.Evolutionary strategy is used for choosing sampling points in GALSA.GALSA works with only O(N) samples which means that GALSA has lower complexity than the famous randomized scheduling algorithm,APSARA.Simulation results show that the delay performance of GALSA is quite competitive with respect to that of APSARA. 展开更多
关键词 switches input-queued randomized algorithm
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Novel and Efficient Randomized Algorithms for Feature Selection 认领 引用 被引量：5
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作者 Zigeng Wang Xia Xiao Sanguthevar Rajasekaran 《Big Data Mining and Analytics》 EI 2020年第3期208-224,共17页
Feature selection is a crucial problem in efficient machine learning,and it also greatly contributes to the explainability of machine-driven decisions.Methods,like decision trees and Least Absolute Shrinkage and Selec... Feature selection is a crucial problem in efficient machine learning,and it also greatly contributes to the explainability of machine-driven decisions.Methods,like decision trees and Least Absolute Shrinkage and Selection Operator(LASSO),can select features during training.However,these embedded approaches can only be applied to a small subset of machine learning models.Wrapper based methods can select features independently from machine learning models but they often suffer from a high computational cost.To enhance their efficiency,many randomized algorithms have been designed.In this paper,we propose automatic breadth searching and attention searching adjustment approaches to further speedup randomized wrapper based feature selection.We conduct theoretical computational complexity analysis and further explain our algorithms’generic parallelizability.We conduct experiments on both synthetic and real datasets with different machine learning base models.Results show that,compared with existing approaches,our proposed techniques can locate a more meaningful set of features with a high efficiency. 展开更多
关键词 feature selection randomized algorithms efficient selection
Prediction of hot-rolled strip crown based on Boruta and extremely randomized trees algorithms 认领 引用 被引量：4
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作者 Li Wang Song-lin He +1 位作者 Zhi-ting Zhao Xian-du Zhang 《Journal of Iron and Steel Research International》 SCIE EI CAS CSCD 2023年第5期1022-1031,共10页
The quality of hot-rolled steel strip is directly affected by the strip crown.Traditional machine learning models have shown limitations in accurately predicting the strip crown,particularly when dealing with imbalanc... The quality of hot-rolled steel strip is directly affected by the strip crown.Traditional machine learning models have shown limitations in accurately predicting the strip crown,particularly when dealing with imbalanced data.This limitation results in poor production quality and efficiency,leading to increased production costs.Thus,a novel strip crown prediction model that uses the Boruta and extremely randomized trees(Boruta-ERT)algorithms to address this issue was proposed.To improve the accuracy of our model,we utilized the synthetic minority over-sampling technique to balance the imbalance data sets.The Boruta-ERT prediction model was then used to select features and predict the strip crown.With the 2160 mm hot rolling production lines of a steel plant serving as the research object,the experimental results showed that 97.01% of prediction data have an absolute error of less than 8 lm.This level of accuracy met the control requirements for strip crown and demonstrated significant benefits for the improvement in production quality of steel strip. 展开更多
关键词 Hot-rolled strip Data improvement Strip crown Feature selection Boruta algorithm Extremely randomized trees algorithm
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Random forest algorithm reveals novel sites in HA protein that shift receptor binding preference of the H9N2 avian influenza virus 认领 引用 被引量：2
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作者 Yuncong Yin Wen Li +7 位作者 Rujian Chen Xiao Wang Yiting Chen Xinyuan Cui Xingbang Lu David M.Irwin Xuejuan Shen Yongyi Shen 《Virologica Sinica》 SCIE CAS CSCD 2025年第1期109-117,共9页
A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,... A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV. 展开更多
关键词 H9N2 Hemagglutinin(HA) Receptor binding preference Random forest algorithm Host shift Interspecies transmission
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Artificial intelligence in the service of entrepreneurial finance:knowledge structure and the foundational algorithmic paradigm 认领 引用
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作者 Robert Kudelić Tamara Šmaguc Sherry Robinson 《Financial Innovation》 2025年第1期2021-2063,共43页
The study conducts a bibliometric review of artificial intelligence applications in two areas:the entrepreneurial finance literature,and the corporate finance literature with implications for entrepreneurship.A rigoro... The study conducts a bibliometric review of artificial intelligence applications in two areas:the entrepreneurial finance literature,and the corporate finance literature with implications for entrepreneurship.A rigorous search and screening of the web of science core collection identified 1,890 journal articles for analysis.The bibliometrics provide a detailed view of the knowledge field,indicating underdeveloped research directions.An important contribution comes from insights through artificial intelligence methods in entrepreneurship.The results demonstrate a high representation of artificial neural networks,deep neural networks,and support vector machines across almost all identified topic niches.In contrast,applications of topic modeling,fuzzy neural networks,and growing hierarchical self-organizing maps are rare.Additionally,we take a broader view by addressing the problem of applying artificial intelligence in economic science.Specifically,we present the foundational paradigm and a bespoke demonstration of the Monte Carlo randomized algorithm. 展开更多
关键词 Bibliometrics Artificial intelligence Entrepreneurship Finance Randomized algorithm
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An Improved Randomized Circle Detection Algorithm Using in Printed Circuit Board Locating Mark 认领 引用 被引量：2
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作者 Jingkun Liu Qi Fan 《Applied Mathematics》 2019年第10期848-861,共14页
This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transfo... This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transform. The experimental results denote that this algorithm can locate the circular mark of Printed Circuit Board (PCB). 展开更多
关键词 Circle Detection Randomized Algorithm Characteristic of Circularity Printed Circuit Board
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A Regularized Randomized Kaczmarz Algorithm for Large Discrete Ill-Posed Problems 认领 引用
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作者 LIU Fengming WANG Zhengsheng +1 位作者 YANG Siyu XU Guili 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2020年第5期787-795,共9页
Tikhonov regularization is a powerful tool for solving linear discrete ill-posed problems.However,effective methods for dealing with large-scale ill-posed problems are still lacking.The Kaczmarz method is an effective... Tikhonov regularization is a powerful tool for solving linear discrete ill-posed problems.However,effective methods for dealing with large-scale ill-posed problems are still lacking.The Kaczmarz method is an effective iterative projection algorithm for solving large linear equations due to its simplicity.We propose a regularized randomized extended Kaczmarz(RREK)algorithm for solving large discrete ill-posed problems via combining the Tikhonov regularization and the randomized Kaczmarz method.The convergence of the algorithm is proved.Numerical experiments illustrate that the proposed algorithm has higher accuracy and better image restoration quality compared with the existing randomized extended Kaczmarz(REK)method. 展开更多
关键词 ill-posed problem Tikhonov regularization randomized extended Kaczmarz(REK)algorithm image restoration
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Anycast service model and its QoS routing algorithm 认领 引用 被引量：14
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作者 WANG Jian xin, CHEN Song qiao, CHEN Jian er 《Journal of Central South University of Technology》 2001年第2期135-139,共5页
In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify ... In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify certain applications. In this paper, the authors described a simple anycast service model in the Internet without significant affecting the routing and protocol processing infrastructure that was already in place, and proposed an anycast QoS routing algorithm for this model. The algorithm used randomized method to balance network load and improve its performance. Several new techniques are proposed in the algorithm, first, theminimum hops for each node are used in the algorithm, which are used as metric for computing the probability of possible out links. The metric is pre computed for each node in the network, which can simplify the network complexity and provide the routing process with useful information. Second, randomness is used at the link level and depends dynamically on the routing configuration. This provides great flexibility for the routing process, prevents the routing process from overusing certain fixed routing paths, and adequately balances the delay of the routing path. the authors assess the quality of QoS algorithm in terms of the acceptance ratio on anycast QoS requests, and the simulation results on a variety of network topologies and on various parameters show that the algorithm has good performances and can balance network load effectively. 展开更多
关键词 QoS anycast service network routing randomized algorithm
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Adaptive adjustment strategy for earth pressure balance(EPB)operation parameters for pre-control of shield tunneling-induced surface settlement:a case study 认领 引用
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作者 Dongsheng WEI Haibin WEI +3 位作者 Zipeng MA Heting WEI Lijie SUN Xiaokun YU 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第7期676-695,I0010-I0023,共20页
During shield tunneling,ground deformation poses significant safety risks.The full optimization strategy ignores interactions between parameters,resulting in suboptimal performance in the pre-control of settlement in ... During shield tunneling,ground deformation poses significant safety risks.The full optimization strategy ignores interactions between parameters,resulting in suboptimal performance in the pre-control of settlement in earth pressure balance shields.To address this problem,this paper proposes an integrated strategy that combines optimization and inversion,minimizing parameter interaction interference through adaptive adjustment of shield operation parameters.This mechanism performs an optimization search on the key operation parameters for settlement control,while the remaining operation parameters are predicted through inversion.Taking the Changchun Metro Line 6 project as an example,a bidirectional long short-term memory(Bi-LSTM)model enhanced by a multi-head self-attention(MHSA)mechanism is used to predict shield tunneling-induced settlement with spatiotemporal sequence dependency relationships.Particle swarm optimization and a random forest algorithm are used for optimization and inversion operations in the integrated mechanism,respectively.Subsequent ring position tests showed that the integrated mechanism-based adaptive adjustment strategy limited the average fluctuation of uncontrollable parameters to±13.95%compared to±34.27%for the full optimization strategy.The actual average settlement was only 3.81 mm compared to 4.72 mm for the full optimization strategy through collaborative parameter adjustment.The application validated the feasibility and applicability of the integrated mechanism,providing important references for the adaptive adjustment of shield parameters and tunnel construction automation. 展开更多
关键词 Pre-control of settlement Optimization and inversion Multi-head self-attention(MHSA) Long short-term memory(LSTM) Random forest(RF)algorithm
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Randomized Generalized Singular Value Decomposition 认领 引用 被引量：3
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作者 Wei Wei Hui Zhang +1 位作者 Xi Yang Xiaoping Chen 《Communications on Applied Mathematics and Computation》 EI 2021年第1期137-156,共20页
The generalized singular value decomposition(GSVD)of two matrices with the same number of columns is a very useful tool in many practical applications.However,the GSVD may suffer from heavy computational time and memo... The generalized singular value decomposition(GSVD)of two matrices with the same number of columns is a very useful tool in many practical applications.However,the GSVD may suffer from heavy computational time and memory requirement when the scale of the matrices is quite large.In this paper,we use random projections to capture the most of the action of the matrices and propose randomized algorithms for computing a low-rank approximation of the GSVD.Serval error bounds of the approximation are also presented for the proposed randomized algorithms.Finally,some experimental results show that the proposed randomized algorithms can achieve a good accuracy with less computational cost and storage requirement. 展开更多
关键词 Generalized singular value decomposition Randomized algorithm Low-rank approximation Error analysis
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A zoning-based machine learning framework for accurate soil organic matter prediction across Mollisol and non-Mollisol regions 认领 引用
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作者 Xue Li Bo Jiang +5 位作者 Depiao Kong Deqiang Zang Ya Chen Changkun Wang Huanjun Liu Chong Luo 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第8期3453-3468,共16页
Soil organic matter(SOM)is a core indicator of soil fertility and ecosystem function.However,in regions where Mollisol and non-Mollisol coexist,high-precision spatial mapping faces significant challenges due to pronou... Soil organic matter(SOM)is a core indicator of soil fertility and ecosystem function.However,in regions where Mollisol and non-Mollisol coexist,high-precision spatial mapping faces significant challenges due to pronounced terrain heterogeneity and redundancy in high-dimensional covariates.This study proposes a"remote sensing zoning-feature selection optimization-random forest(RSZ-FSO-RF)"framework.By integrating Landsat-8 multi-temporal imagery from 2014-2023 with topographic and climatic factors,and leveraging the Google Earth Engine(GEE)platform,it achieves highprecision remote sensing zoning of Mollisol and non-Mollisol areas(overall accuracy:92.13%,Kappa coefficient:0.70).Subsequently,local Random Forest(RF)regression models were established within each zone for SOM prediction,with predictive variables optimized using recursive feature elimination(RFE).Results demonstrate that compared to FAOzone-based modeling,the RSZ-FSO-RF framework significantly enhances prediction accuracy(R2=0.619,RMSE=6.849 g kg-1).And further feature optimization continued to enhance model performance(R2=0.627,RMSE=6.781 g kg-1).Notably,optimal predictor combinations varied significantly across zones,with SOM spatial variability generally higher in non-Mollisol areas than in Mollisol regions.By organically integrating remote sensing zoning with feature selection,this framework effectively mitigates covariate redundancy while accounting for local heterogeneity,significantly enhancing the accuracy and stability of high-resolution SOM mapping.Furthermore,this study provides scientific basis and decision support for soil resource management and sustainable agricultural development under complex topographic conditions. 展开更多
关键词 soil organic matter remote sensing zoning feature selection algorithm random forest algorithm prediction
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A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm 认领 引用 被引量：11
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作者 Tie Yan Rui Xu +2 位作者 Shi-Hui Sun Zhao-Kai Hou Jin-Yu Feng 《Petroleum Science》 SCIE EI CAS CSCD 2024年第2期1135-1148,共14页
Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face ... Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation. 展开更多
关键词 Intelligent drilling Closed-loop drilling Lithology identification Random forest algorithm Feature extraction
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Random State Approach to Quantum Computation of Electronic-Structure Properties 认领 引用
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作者 Yiran Bai Feng Xiong Xueheng Kuang 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第1期89-104,共16页
Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and v... Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials. 展开更多
关键词 periodic materials random state circuit random state quantum algorithms electronic structure properties density states aperiodic materials quantum algorithms quantum computation
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Prostate cancer prediction forest algorithm that takes using the random into account transrectal ultrasound findings, age, and serum levels of prostate-specific antigen 认领 引用 被引量：7
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作者 Li-Hong Xiao Pei-Ran Chen +4 位作者 Zhong-Ping Gou Yong-Zhong Li Mei Li Liang-Cheng Xiang Ping Feng 《Asian Journal of Andrology》 SCIE CAS CSCD 2017年第5期586-590,共5页
The aim of this study is to evaluate the ability of the random forest algorithm that combines data on transrectal ultrasound findings, age, and serum levels of prostate-specific antigen to predict prostate carcinoma. ... The aim of this study is to evaluate the ability of the random forest algorithm that combines data on transrectal ultrasound findings, age, and serum levels of prostate-specific antigen to predict prostate carcinoma. Clinico-demographic data were analyzed for 941 patients with prostate diseases treated at our hospital, including age, serum prostate-specific antigen levels, transrectal ultrasound findings, and pathology diagnosis based on ultrasound-guided needle biopsy of the prostate. These data were compared between patients with and without prostate cancer using the Chi-square test, and then entered into the random forest model to predict diagnosis. Patients with and without prostate cancer differed significantly in age and serum prostate-specific antigen levels （P 〈 0.001）, as well as in all transrectal ultrasound characteristics （P 〈 0.05） except uneven echo （P = 0.609）. The random forest model based on age, prostate-specific antigen and ultrasound predicted prostate cancer with an accuracy of 83.10%, sensitivity of 65.64%, and specificity of 93.83%. Positive predictive value was 86.72%, and negative predictive value was 81.64%. By integrating age, prostate-specific antigen levels and transrectal ultrasound findings, the random forest algorithm shows better diagnostic performance for prostate cancer than either diagnostic indicator on its own. This algorithm may help improve diagnosis of the disease by identifying patients at high risk for biopsy. 展开更多
关键词 diagnosis prostate cancer prostate-specific antigen random forest algorithm transrectal ultrasound characteristics
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Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China 认领 引用 被引量：9
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作者 Huiling Tian Jianhua Zhu +8 位作者 Xiao He Xinyun Chen Zunji Jian Chenyu Li Qiangxin Ou Qi Li Guosheng Huang Changfu Liu Wenfa Xiao 《Forest Ecosystems》 SCIE CSCD 2022年第3期396-406,共11页
Estimating the volume growth of forest ecosystems accurately is important for understanding carbon sequestration and achieving carbon neutrality goals.However,the key environmental factors affecting volume growth diff... Estimating the volume growth of forest ecosystems accurately is important for understanding carbon sequestration and achieving carbon neutrality goals.However,the key environmental factors affecting volume growth differ across various scales and plant functional types.This study was,therefore,conducted to estimate the volume growth of Larix and Quercus forests based on national-scale forestry inventory data in China and its influencing factors using random forest algorithms.The results showed that the model performances of volume growth in natural forests(R2=0.65 for Larix and 0.66 for Quercus,respectively)were better than those in planted forests(R2=0.44 for Larix and 0.40 for Quercus,respectively).In both natural and planted forests,the stand age showed a strong relative importance for volume growth(8.6%–66.2%),while the edaphic and climatic variables had a limited relative importance(<6.0%).The relationship between stand age and volume growth was unimodal in natural forests and linear increase in planted Quercus forests.And the specific locations(i.e.,altitude and aspect)of sampling plots exhibited high relative importance for volume growth in planted forests(4.1%–18.2%).Altitude positively affected volume growth in planted Larix forests but controlled volume growth negatively in planted Quercus forests.Similarly,the effects of other environmental factors on volume growth also differed in both stand origins(planted versus natural)and plant functional types(Larix versus Quercus).These results highlighted that the stand age was the most important predictor for volume growth and there were diverse effects of environmental factors on volume growth among stand origins and plant functional types.Our findings will provide a good framework for site-specific recommendations regarding the management practices necessary to maintain the volume growth in China's forest ecosystems. 展开更多
关键词 Stand volume growth Stand origin Plant functional type National forest inventory data Random forest algorithms
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Tilt Measurement Method of Wooden Columns in Traditional Timber Buildings Based on Adaptive RANSAC and PCA Method 认领 引用
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作者 Minyan Zhan Wei Yang +2 位作者 Minghao Wu Hsin-Yi Wang Yu-Hsien Ho 《Structural Durability & Health Monitoring》 EI 2026年第3期395-414,共20页
The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China.However,accurate measurement is challenging because these columns typically exhibit na... The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China.However,accurate measurement is challenging because these columns typically exhibit natural tapering,with diameters decreasing from the base to the top,and surface irregularities such as artificial cuts,cracks,and knots.Both the intrinsic geometric characteristics and surface defects reduce the precision of coordinate acquisition and the reliability of inclination estimation.To overcome these limitations,this study proposes a novel inclination measurement method for wooden columns in traditional timber buildings based on multi-section measurement and spatial line fitting.An adaptive random sample consensus algorithm is employed to effectively remove outliers induced by surface damage and measurement noise.Subsequently,principal component analysis is used to fit a three-dimensional spatial line through the center points of multiple cross-sections,enabling accurate computation of the inclination angle while accounting for structural imperfections.Moreover,the effects of damage defects,the number of measuring points,the measurement range,and the number of selected cross-sections on measurement accuracy are systematically investigated through statistical analysis,and corresponding recommended values for engineering practice are provided.The proposed method offers an efficient and reliable solution for inclination measurement,supporting the inspection and structural safety assessment of traditional timber columns. 展开更多
关键词 Traditional timber building inclination measurement of wooden column adaptive random sample consensus algorithm principal component analysis
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