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Coherence and decoherence in generalized Shor's algorithm 认领 引用
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作者 Linlin Ye Zhaoqi Wu Nanrun Zhou 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第6期660-673,共14页
Quantum coherence constitutes a fundamental physical mechanism essential to the study of quantum algorithms.We study coherence and decoherence in the generalized Shor's algorithm where the register A is initialize... Quantum coherence constitutes a fundamental physical mechanism essential to the study of quantum algorithms.We study coherence and decoherence in the generalized Shor's algorithm where the register A is initialized in an arbitrary pure state,or the combined register AB is initialized in a pseudo-pure state,which encompasses the standard Shor's algorithm as a special case.We derive both lower and upper bounds on the performance of the generalized Shor's algorithm,and establish the relation between the probability of calculating the order r when register AB is initialized in a pseudo-pure state and that when register A is initialized in an arbitrary pure state.Moreover,we study coherence and decoherence in the noisy Shor's algorithm and give a lower bound on the probability that we can calculate the order r. 展开更多
关键词 Shor’S algorithm coherence decoherence success probability
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Three-party semi-quantum dialogue enhanced with Grover's algorithm based encoding and hypergraph access control 认领 引用
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作者 Rui Tao Jin-Zhe Jiang Zhi-Hua Zhang 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第7期435-447,共13页
We introduce a new three-party semi-quantum dialogue(3P-SQD)protocol that combines GHZ-state-based semiquantum communication,a Grover's algorithm-driven 2-bit encoding scheme,and hypergraph-based access control.In... We introduce a new three-party semi-quantum dialogue(3P-SQD)protocol that combines GHZ-state-based semiquantum communication,a Grover's algorithm-driven 2-bit encoding scheme,and hypergraph-based access control.In each round,the fully quantum participant Alice sends two bits,whereas the semi-quantum participants Bob and Charlie,restricted to semi-quantum operations such as measurements in the computational basis and reflection,each transmit one bit.The protocol incorporates probe state checking,Grover's algorithm-based encoding,and hypergraph-based authorization.It achieves information-theoretic security and controlled access,while preserving high message throughput and imposing no additional requirements on the semi-quantum users. 展开更多
关键词 semi-quantum dialogue Grover’s algorithm based encoding hypergraph access structure quantum communication
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Distributed Kuperberg's algorithm 认领 引用
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作者 Peng-Yu Yang Xin Zhang Song Lin 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第3期220-227,共8页
As an important quantum cryptanalysis algorithm,Kuperberg's algorithm efficiently addresses the dihedral hidden subgroup problem with sub-exponential acceleration.However,when dealing with large numbers,the algori... As an important quantum cryptanalysis algorithm,Kuperberg's algorithm efficiently addresses the dihedral hidden subgroup problem with sub-exponential acceleration.However,when dealing with large numbers,the algorithm demands a deeper quantum circuit depth,rendering its implementation on current quantum devices prone to noise interference and thereby significantly reducing its efficiency.To mitigate this challenge,this paper proposes a distributed Kuperberg's algorithm.It decomposes the original function into sub-functions which can be executed on different nodes in parallel.The implementation of these sub-functions necessitates a shallower quantum circuit depth and a reduced number of qubits when contrasted with the execution of the original function.Furthermore,the proposed algorithm can be directly generalized to an arbitrary number of nodes by adjusting the quantity of input qubits.The utilization of multi-node parallel processing makes the proposed algorithm a linear enhancement in query complexity relative to the original algorithm.To validate the feasibility and demonstrate the superiority of our algorithm,experiments are conducted on the Qiskit platform. 展开更多
关键词 Kuperberg’s algorithm distributed quantum computing function decomposition quantum circuit depth
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Machine learning supervised algorithms for gas hydrate identification and saturation estimation in marine reservoirs using well log data:A case study of NGHP-01-19B 认领 引用
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作者 Yi-fan Wu Zheng Su +5 位作者 Takeshi Tsuji Dai-dai Wu Guang-rong Jin Chao Yang Chuang-ji Feng Neng-you Wu 《China Geology》 CAS CSCD 2026年第3期519-534,I0023-I0027,共16页
Gas hydrates are increasingly recognized as a significant unconventional energy resource and a key factor in marine geohazards and the global carbon cycle.However,accurately identifying and quantifying hydrate-bearing... Gas hydrates are increasingly recognized as a significant unconventional energy resource and a key factor in marine geohazards and the global carbon cycle.However,accurately identifying and quantifying hydrate-bearing formations remains challenging due to complex geophysical signatures and heterogeneous distribution.This study evaluates twelve supervised machine learning(ML)algorithms for two key tasks:Classification of hydrate-bearing layers and regression-based estimation of hydrate saturation,using well log and pore-water geochemical data from Site NGHP-01-19B.Two physically independent labeling frameworks are employed:One based on Archie's law using resistivity(1350 samples,29%hydratebearing),and another based on a three-phase velocity model(890 samples,25%hydrate-bearing).A diverse set of models,including tree-based ensembles(Decision Tree,Random Forest,GBDT,XGBoost,Light GBM,Cat Boost,Bagging,Ada Boost),kernel methods(SVM,SVR),instance-based learning(KNN),neural networks(MLP),and Gaussian Process models(GPR,GPC),are systematically compared using cross-validation and grid search.Ensemble methods consistently performed best in classification,with Ada Boost and GBDT,achieving test accuracies above 0.94(Archie)and 0.98(velocity-based).For regression,GPR delivered the most accurate hydrate saturation estimates(R2>0.99),while GBDT and Random Forest provided a strong balance of accuracy and computational efficiency.Notably,depth below seafloor(TDEP),though not a direct geophysical input,significantly enhanced model performance by acting as a proxy for stratigraphic and thermodynamic conditions.Group-based validation confirmed that random-sample splitting overestimates performance due to depth-wise autocorrelation,highlighting the importance of geologically informed model assessment.Overall,the consistent performance of ML models across both labeling schemes and input feature sets underscores their robustness and transferability,supporting their use as a reliable toolset for offshore gas hydrate reservoir characterization. 展开更多
关键词 Gas hydrate Machine learning algorithm Classification Regression Well log data Archie’s law Marine geohazards Global carbon cycle
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Advanced 3D Wind Farm Layout Optimization Framework via Power-Law Perturbation-Based Genetic Algorithm 认领 引用
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作者 Jiaru Yang Yaotong Song +3 位作者 Jun Tang Weiping Ding Zhenyu Lei Shangce Gao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第11期2314-2328,共15页
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz... The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency. 展开更多
关键词 3D wake model China’s southeastern coast metaheuristic offshore wind farm power-law perturbation-based genetic algorithm(PPGA)
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Fast Mixture Distribution Optimization for Rain-Flow Matrix of a Steel Arch Bridge by REBMIX Algorithm 认领 引用
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作者 Yuliang He Weihong Lou +1 位作者 Da Hang Youhua Su 《Structural Durability & Health Monitoring》 EI 2025年第4期887-902,共16页
The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stre... The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stress spectrum model is crucial for further fatigue reliability analysis.This study investigates the performance of the REBMIX algorithm in modeling both univariate(stress range)and multivariate(stress range and mean stress)distributions of the rain-flowmatrix for a steel arch bridge,usingAkaike’s Information Criterion(AIC)as a performance metric.Four types of finitemixture distributions—Normal,Lognormal,Weibull,and Gamma—are employed tomodel the stress range.Additionally,mixed distributions,including Normal-Normal,Lognormal-Normal,Weibull-Normal,and Gamma-Normal,are utilized to model the joint distribution of stress range and mean stress.The REBMIX algorithm estimates the number of components,component weights,and component parameters for each candidate finite mixture distribution.The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values.Furthermore,the algorithm exhibits superior computational efficiency compared to traditional methods,making it highly suitable for practical applications. 展开更多
关键词 Steel bridge stress spectrum finite mixture distribution REBMIX algorithm Akaike’s information criterion
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基于PSO算法的无人平台无线电能传输系统参数优化 认领 引用 被引量：2
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作者 魏曙光 许非凡 +1 位作者 李嘉麒 袁东 《电源学报》 CSCD 北大核心 2026年第5期275-285,共11页
无人平台具有体积小、成本低、无需载员操作等优势,广泛应用于各类军事任务中。目前,无人平台主要以电能作为能源,其对可靠电能传输方式的需求不断增大,在人员无法参与、充电接口不适配、充电流程效率低等场合,有线充电或更换电池存在弊... 无人平台具有体积小、成本低、无需载员操作等优势,广泛应用于各类军事任务中。目前,无人平台主要以电能作为能源,其对可靠电能传输方式的需求不断增大,在人员无法参与、充电接口不适配、充电流程效率低等场合,有线充电或更换电池存在弊端,无法满足无人平台对电能传输的需求。针对无人平台无线电能传输需求设计系统结构,并基于该结构提出了一种基于粒子群优化PSO(particle swarm optimization)算法的参数优化方法。通过对无人平台无线电能传输系统补偿电路、耦合线圈、储能器件结构及特性进行分析,提出系统参数优化数学模型的优化目标及功率、效率、电流3个方面的约束条件,设计基于PSO算法的无人平台无线电能传输系统参数优化方法的算法流程。通过算法仿真与样机实验相结合的方法进行验证,结果表明,提出的基于PSO算法的无人平台无线电能传输系统参数优化方法能够降低系统输出电压和功率、效率随负载电阻和耦合系数变化的波动幅度,提高无人平台无线电能传输系统的鲁棒性和环境适应性。 展开更多
关键词 无线电能传输 LCC/S补偿电路 参数优化方法 粒子群优化算法
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基于图像信息算法的2024年新疆乌什MS7.1地震回溯性预测研究 认领 引用 被引量：1
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作者 袁伏全 黄浩 +2 位作者 徐玮阳 张晓清 刘兴盛 《地震研究》 CSCD 北大核心 2026年第2期198-206,共9页
使用1970年以来新疆天山地震带及邻区的地震目录资料,基于图像信息(PI)算法,计算得到2016—2028年该地区逐年滑动的预测窗PI热点分布图像,并使用工作特征图表法(ROC)和R值评分法对PI算法的预测效能进行了检验。结果表明:①在2020—2024... 使用1970年以来新疆天山地震带及邻区的地震目录资料,基于图像信息(PI)算法,计算得到2016—2028年该地区逐年滑动的预测窗PI热点分布图像,并使用工作特征图表法(ROC)和R值评分法对PI算法的预测效能进行了检验。结果表明:①在2020—2024年回溯性预测图像中,2024年新疆乌什MS7.1地震震中区域存在PI热点,具有较强的发震地点指示意义。②在5个回溯性预测时间窗(2016—2020年、2017—2021年、2018—2022年、2019—2023年、2020—2024年)内的PI热点图像演化过程中,乌什MS7.1地震震中附近PI热点表现为“出现—逐步密集增强”,发震概率增大,该热点附近发震紧迫性和地震危险性增强。③ROC检验和R值评分显示,PI算法优于随机预测方法。④综合热点信息演化图像分析得到,南天山地震带的西南端强震危险性较高。 展开更多
关键词 乌什MS7.1地震 PI算法 回溯性预测 地震热点 ROC检验
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基于改进YOLOv5-s的交通场景小目标检测算法 认领 引用 被引量：1
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作者 王坤 冯康威 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2026年第4期1015-1027,共13页
针对交通标志和交通灯等交通场景小目标特征不明显导致检测困难的问题,提出基于改进YOLOv5-s的交通场景小目标检测算法。设计特征补充模块(FSM),通过进一步获取浅层细节信息对相邻的深层检测层进行特征补充,有效提高了小目标的检测效果... 针对交通标志和交通灯等交通场景小目标特征不明显导致检测困难的问题,提出基于改进YOLOv5-s的交通场景小目标检测算法。设计特征补充模块(FSM),通过进一步获取浅层细节信息对相邻的深层检测层进行特征补充,有效提高了小目标的检测效果,并通过相邻层间的矩阵运算避免了特征冗余;设计有效融合模块(EFM),分别处理特征金字塔融合时的横向浅层特征和上采样特征,缓解二者之间的特征冲突,使其更有效的融合;提出超级增强交并比(SEIOU)损失计算方式,通过添加真实框和预测框主对角之间的距离度量,改善回归效果,提升检测精度。在CCTSDB、S2TLD、TLD和PASCAL VOC数据集上进行实验,结果表明:所提算法在精度上分别提升了2.54%、3.62%、4.33%和2.01%,检测速度达到了113帧/s,适用于实际交通场景下的检测任务。 展开更多
关键词 YOLOv5-s算法 小目标检测 特征补充 特征融合 损失函数
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在片S参数校准技术比较分析 认领 引用
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作者 霍晔 王一帮 +6 位作者 孙静 刘晨 郭诚 王海 王浩 张立飞 吴爱华 《计量学报》 CSCD 北大核心 2026年第7期1069-1074,共6页
针对微波毫米波芯片测试中的关键在片S参数校准技术,分析与比较了常用的SOLT、SOLR、LRM、LRRM、TRL和Multiline-TRL校准算法,阐述了每种算法的误差模型、频率适用范围,从校准测试准确度和效率方面论述了各自的优势和缺点。描述了各算... 针对微波毫米波芯片测试中的关键在片S参数校准技术,分析与比较了常用的SOLT、SOLR、LRM、LRRM、TRL和Multiline-TRL校准算法,阐述了每种算法的误差模型、频率适用范围,从校准测试准确度和效率方面论述了各自的优势和缺点。描述了各算法所对应在片校准件的组成、参数定义及用途。在1~67 GHz频段,在相同的在片S参数测试系统上,用国际上惯用的校准比较方法对上述校准技术进行了验证,以准确度高的Multiline-TRL算法为基准,计算了测试无源芯片时其他算法与基准算法S参数的最大偏差,为不同在片校准测试场景下校准技术的选择提供参考。 展开更多
关键词 无线电计量 在片S参数 校准算法 校准件 误差模型 Multiline-TRL算法
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基于BP算法的复合域大规模S盒FPGA优化与实现 认领 引用
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作者 张磊 代景晨 +3 位作者 洪睿鹏 肖超恩 李国元 王建新 《现代电子技术》 北大核心 2026年第13期96-104,共9页
为解决MK-3算法大规模S盒硬件实现资源占用量大、同构函数组合数爆炸的问题,文中提出一种基于XOR数量最少的S盒硬件实现优化方法。首先,通过多项式基的复合域GF(((24)2)2)将S盒优化方法转换为同构矩阵与同构逆矩阵二元矩阵乘XO... 为解决MK-3算法大规模S盒硬件实现资源占用量大、同构函数组合数爆炸的问题,文中提出一种基于XOR数量最少的S盒硬件实现优化方法。首先,通过多项式基的复合域GF(((24)2)2)将S盒优化方法转换为同构矩阵与同构逆矩阵二元矩阵乘XOR数量最小问题;其次,基于BP算法筛选得到最优同构矩阵和同构逆矩阵;最后,采用Vivado开发环境进行FPGA实现。实验结果表明,基于BP算法优化的S盒FPGA实现时钟频率LUT达到了0.41621,与已有的方案相比,该方法在降低硬件资源消耗的同时提高了时钟频率,取得了较好的优化效果。 展开更多
关键词 分组密码算法 S盒 BP算法 MK-3算法 同构函数 有限域 多项式基 FPGA
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一种轻量级光伏MPPT算法S&M的设计 认领 引用
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作者 张晓新 王俊豪 +1 位作者 侯冶 王宇鹏 《重庆理工大学学报（自然科学）》 CAS 北大核心 2026年第6期221-227,共7页
针对分布式光伏中常见的最大功率点跟踪(maximum power point tracking,MPPT)算法难以同时解决组件本身失配与组件间失配的问题,提出一种轻量级MPPT算法——搜寻维持法(search and maintain,S&M)。该算法在搜寻阶段通过一次遍历快... 针对分布式光伏中常见的最大功率点跟踪(maximum power point tracking,MPPT)算法难以同时解决组件本身失配与组件间失配的问题,提出一种轻量级MPPT算法——搜寻维持法(search and maintain,S&M)。该算法在搜寻阶段通过一次遍历快速获取光伏组件的功率,并在确定全局最大功率点后切换到维持阶段;在维持阶段,通过PID微调,使工作点稳定运行在最大功率点附近。该算法计算量小,便于在各类嵌入式平台中实现。Simulink仿真结果表明,S&M算法相较于扰动观察法(perturb and observe,P&O)能有效缓解组件本身失配下的多峰值问题,相较于粒子群优化(particle swarm optimization,PSO)算法能够抑制组件间失配时多组件并行MPPT所引起的相互干扰。其全局最大功率点跟踪成功率达到99%以上,收敛时间可缩短至0.01 s;通过实物验证进一步证明了该算法在实际系统中能够实现多组件协同的全局最大功率点跟踪。 展开更多
关键词 分布式光伏 最大功率点跟踪 搜寻维持法 多峰值 轻量级算法
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面向中小企业的S-ARIZ算法——TRIZ理论的简化与实践探索 认领 引用
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作者 杨得成 刁幕鹏 曹福全 《黑河学院学报》 2026年第5期19-22,77,共4页
在TRIZ理论“本土化”进程中,助力中小企业提升技术创新能力至关重要。传统TRIZ理论科学性虽强,但因体系复杂,在推广上受到了限制。S-TRIZ的核心特征,即简约化和结构化,以此构建基于此衍生的S-ARIZ算法。S-ARIZ算法聚焦矛盾、理想解与... 在TRIZ理论“本土化”进程中,助力中小企业提升技术创新能力至关重要。传统TRIZ理论科学性虽强,但因体系复杂,在推广上受到了限制。S-TRIZ的核心特征,即简约化和结构化,以此构建基于此衍生的S-ARIZ算法。S-ARIZ算法聚焦矛盾、理想解与资源三大核心要素,通过模块化设计实现高效灵活的问题解决流程,尤其适用于中小企业的技术创新场景,可助力其突破创新瓶颈,推动我国创新实践迈向新高度。 展开更多
关键词 TRIZ本土化 TRIZ S-TRIZ S-ARIZ算法 中小企业创新
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基于S-ALE算法的巷道孤石光面爆破围岩损伤规律研究 认领 引用
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作者 黄永辉 荆蕊 +2 位作者 张译尹 段强坤 曹永炜 《爆破》 CAS CSCD 北大核心 2026年第2期160-169,178,共10页
巷道孤石是地下工程中的重大安全隐患,针对爆破法处理孤石的效果及对围岩损伤的影响开展研究,采用光面爆破理论和近年来刚产生的S-ALE算法,依托云南某地下金属矿山巷道工程,构建等比例三维数值仿真模型,系统地分析研究了光面爆破技术处... 巷道孤石是地下工程中的重大安全隐患,针对爆破法处理孤石的效果及对围岩损伤的影响开展研究,采用光面爆破理论和近年来刚产生的S-ALE算法,依托云南某地下金属矿山巷道工程,构建等比例三维数值仿真模型,系统地分析研究了光面爆破技术处理巷道孤石时的围岩损伤随不同线装药密度和炮孔间距的变化规律。研究结果表明:孤石光面爆破围岩损伤度随爆心距增大呈“反S”型下降;围岩的最大损伤深度随线装药密度增加呈线性增大变化,随炮孔间距增大呈波动变化,且在炮孔间距为0.36 m和0.40 m时分别达到最大值和最小值;围岩损伤变化对线装药密度的敏感性远大于炮孔间距,在考虑爆破效果和炸药使用量的情况下,最优爆破参数为线装药密度0.30 kg/m(装药不耦合系数1.43)和炮孔间距0.40 m;由于孤石大临空面积的特性,与常规光面爆破相比其围岩最大损伤深度明显偏小,这与垂直洞轮廓线临空方向和沿洞轮廓线临空方向的塑性应变下降率基本一致。相关研究结果能够为实际工程提供技术指导。 展开更多
关键词 线装药密度 炮孔间距 围岩损伤 数值模拟 S-ALE算法
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基于元启发式算法优化深度学习模型的污水格栅间H2S浓度预测 认领 引用
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作者 娄和壮 孙惠 高婧琦 《中国环境科学》 EI CAS CSCD 北大核心 2026年第7期3727-3736,共10页
针对污水格栅间H2S浓度动态变化复杂、传统监测方法难以实现精准预测的问题,构建了一种基于长短期记忆网络(LSTM)与门控循环单元(GRU)的混合深度学习模型,并进一步提出了一种改进鲸鱼优化算法(IWOA)对混合模型超参数进行自适应优化.... 针对污水格栅间H2S浓度动态变化复杂、传统监测方法难以实现精准预测的问题,构建了一种基于长短期记忆网络(LSTM)与门控循环单元(GRU)的混合深度学习模型,并进一步提出了一种改进鲸鱼优化算法(IWOA)对混合模型超参数进行自适应优化.通过引入Tent混沌映射实现种群均匀初始化,结合Levy飞行机制与自适应权重因子,增强算法全局探索与局部开发能力.结果表明:IWOA-LSTM-GRU在测试集上R2达到0.997,MSE与RMSE分别降低至0.021×10-6,0.145×10-6,显著优于雀鸟搜索算法(SSA)、萤火虫算法(FA)和冬虫夏草优化算法(CFO)元启发式算法对应的混合模型,且准确捕捉了H2S浓度瞬态尖峰与缓变过程,其报警实现率Ra(5.55%)与实际值(5.58%)一致.本研究为污水格栅间H2S浓度高精度预测与安全监测系统优化提供了可靠的理论工具与方法支撑. 展开更多
关键词 长短期记忆网络 鲸鱼优化算法 冬虫夏草优化算法 污水格栅间 H2S浓度
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Fed-HOER: Federated Hybrid-Optimized Emotion Recognition Framework Using DBO-FLA Metaheuristic Optimization 认领 引用
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作者 Mohammed Shukur Alfaras Oguz Karan +1 位作者 Sefer Kurnaz Ayca Kurnaz Turkben 《Computers, Materials & Continua》 SCIE EI 2026年第8期1673-1699,共27页
Despite deep learning’s high precision in emotion identification,centralized training is associated with privacy and scalability concerns.The privacy-preserving federated learning model,Federated Hybrid-Optimized Emo... Despite deep learning’s high precision in emotion identification,centralized training is associated with privacy and scalability concerns.The privacy-preserving federated learning model,Federated Hybrid-Optimized Emotion Recognition(Fed-HOER),introduced in this paper is an auto-tuning hyperparameters optimizer based on a hybrid Dung Beetle Optimizer-Fick’s Law Algorithm(DBO-FLA)optimizer.The global and local searches are optimized at two levels,and validation loss is minimized by 22%–24%without sharing raw data.The experiments on Extended Cohn–Kanade(CK+),Japanese Female Facial Expressions(JAFFE),and Karolinska Directed Emotional Faces(KDEF)exhibit a high generalization rate with a mean accuracy of 98.14.The findings demonstrate that Fed-HOER is statistically significantly better than baseline configurations.The results show that the suggested framework offers a favorable trade-off between predictive accuracy and privacy protection,which is why it can be used in the healthcare,educational,and other emotion-related fields. 展开更多
关键词 Emotion recognition affective computing federated learning Dung Beetle Optimizer(DBO) Fick’s Law Algorithm(FLA) hybrid metaheuristic optimization privacy preservation convolutional neural networks(CNN)
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Biases of large language models in diagnosing Cushing’s syndrome 认领 引用
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作者 Christos Savvidis Costas Liakopoulos Ioannis Ilias 《World Journal of Methodology》 2026年第2期63-71,共9页
The diagnosis of endogenous Cushing’s syndrome(CS)can be complicated and often delayed,given its low incidence(estimated globally at 1.8 cases to 4.5 cases per million people per year)and its clinical features that m... The diagnosis of endogenous Cushing’s syndrome(CS)can be complicated and often delayed,given its low incidence(estimated globally at 1.8 cases to 4.5 cases per million people per year)and its clinical features that mimic far more prevalent metabolic disorders,such as central obesity,hypertension,and glucose intolerance.In clinical practice,physicians rely on cognitive heuristics that are prone to error,contributing to diagnostic delays(on average around 34 months pass from symptom onset to diagnosis of CS).Large language models and machine learning algorithms could be potential decision-support tools for screening and differential diagnosis of CS.However,these systems are at risk of inheriting and even amplifying existing cognitive biases and data-driven distortions embedded in their training data.Machine learning models designed for CS could be vulnerable to methodological flaws,notably spectrum bias and the exclusion of clinically relevant demographic variables,demanding attention from the endocrine and medical informatics communities.This paper examines how cognitive and algorithmic biases intersect in diagnostic models for CS,highlighting parallels between human diagnostic heuristics(e.g.,anchoring,availability,and framing)and datadriven distortions(e.g.,spectrum and measurement bias)in artificial intelligence. 展开更多
关键词 Cushing’s syndrome Diagnostic bias Large language models Spectrum bias Algorithmic fairness
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基于S波信号的高铁地震预警P波识别修正算法研究 认领 引用
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作者 李慧 慕阳 曾鹏 《铁道标准设计》 北大核心 2026年第4期77-84,共8页
在中国地震频发、铁路网络遍布全国的背景下,地震灾害对铁路基础设施和高速列车运行安全构成重大威胁。因此,为降低地震带来的潜在损害并提高铁路运输的安全性,提升高速铁路地震预警系统的报警准确性显得尤为重要。针对高速铁路地震监... 在中国地震频发、铁路网络遍布全国的背景下,地震灾害对铁路基础设施和高速列车运行安全构成重大威胁。因此,为降低地震带来的潜在损害并提高铁路运输的安全性,提升高速铁路地震预警系统的报警准确性显得尤为重要。针对高速铁路地震监测系统在复杂外部环境干扰下可靠运行的挑战,尤其是干扰信号混入地震实时监测信号导致地震预警不准确的问题,提出一种基于S波的P波识别修正方法。该方法旨在缓解地震预警过程中出现的P波捡拾错误问题,从而提高预警的准确性。通过综合考虑偏振特征、信噪比特征以及最大振幅比特征等多个识别修正参数,并结合小波分解法与AIC法,对识别错误的P波进行修正。本研究广泛使用国内外多种地震数据集,对不同地域地震数据的识别能力进行全面对比分析,特别关注P波捡拾错误地震数据的特征。实验结果显示,在561次样本数据中,共识别修正230次P波识别错误事件,同时维持判定其余331次P波识别准确事件。研究所述的技术可以作为一个并行处理模块,集成到现有的地震预警系统中,实时接收并处理数据,有效识别P波捡拾错误信号并输出准确的P波信息,确保地震实时监测系统报警信息的高准确性。 展开更多
关键词 高速铁路 地震预警 预警算法 P波识别 S波信号 修正算法
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顾及水汽垂直变化特征的GNSS湿延迟模型构建 认领 引用
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作者 孔文静 罗孝文 郭杭 《导航定位学报》 CSCD 北大核心 2026年第2期35-43,共9页
为了进一步提高全球导航卫星系统(GNSS)大气反演技术中天顶湿延迟(ZWD)在气象领域的预测精度,提出一种顾及水汽垂直变化特征的GNSS湿延迟模型:基于极限梯度提升(XGBoost)算法构建ZWD预测模型;并通过计算水汽衰减因子和比湿分别与ZWD的... 为了进一步提高全球导航卫星系统(GNSS)大气反演技术中天顶湿延迟(ZWD)在气象领域的预测精度,提出一种顾及水汽垂直变化特征的GNSS湿延迟模型:基于极限梯度提升(XGBoost)算法构建ZWD预测模型;并通过计算水汽衰减因子和比湿分别与ZWD的相关系数,将这2个关键水汽特征参数纳入模型输入。实验结果表明,8输入模型在预测精度和稳定性上优于6输入模型,均方误差(MSE)、均方根误差(RMSE)和平均绝对误差(MAE)分别降低12.36%、6.31%和4.01%,可显著提升模型对大气水汽变化的敏感性;在中国北方和中西部区域,模型预测效果更优;利用2024年探空数据验证,XGBoost模型的偏差相较于萨斯塔莫宁(Saastamoinen)模型、霍普菲尔德(Hopfield)模型、第三代全球气压和温度模型(GPT3),分别减小89.3%、90.3%、3.7%,且RMSE亦优于其他模型,提升幅度分别为20.9%、26.4%、9.0%;在高海拔地区,XGBoost模型的表现更为稳定,其偏差和RMSE均显著减小。 展开更多
关键词 天顶湿延迟(ZWD) 极限梯度提升算法(XGBoost) 全球导航卫星系统(GNSS)气象学 大气反演 导航卫星
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Analysis of Innovative Quantum Optimization Solutions for Shor’s Period Finding Algorithm Applied to the Computation of ax mod 15 认领 引用
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作者 Kaleb Dias Antoine KODO Eugène CEZIN 《Journal of Quantum Computing》 2025年第1期17-38,共22页
In the rapidly evolving domain of quantum computing,Shor’s algorithm has emerged as a groundbreaking innovation with far-reaching implications for the field of cryptographic security.However,the efficacy of Shor’s a... In the rapidly evolving domain of quantum computing,Shor’s algorithm has emerged as a groundbreaking innovation with far-reaching implications for the field of cryptographic security.However,the efficacy of Shor’s algorithm hinges on the critical step of determining the period,a process that poses a substantial computational challenge.This article explores innovative quantum optimization solutions that aim to enhance the efficiency of Shor’s period finding algorithm.The article focuses on quantum development environments,such as Qiskit and Cirq.A detailed analysis is conducted on three notable tools:Qiskit Transpiler,BQSKit,and Mitiq.The performance of these tools is evaluated in terms of execution time,precision,resource utilization,the number of quantum gates,circuit synthesis optimization,error mitigation,and qubit fidelity.Through rigorous case studies,we highlight the strengths and limitations of these tools,shedding light on their potential impact on integer factorization and cybersecurity.Our findings underscore the importance of quantum optimization and lay the foundation for future developments in quantum algorithmic enhancements,particularly within the Qiskit and Cirq quantum development environments. 展开更多
关键词 Quantum computing shor’s algorithm quantum optimization cryptographic security
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