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Hybrid Gene Selection Methods for High-Dimensional Lung Cancer Data Using Improved Arithmetic Optimization Algorithm
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作者 Mutasem K.Alsmadi 《Computers, Materials & Continua》 SCIE EI 2024年第6期5175-5200,共26页
Lung cancer is among the most frequent cancers in the world,with over one million deaths per year.Classification is required for lung cancer diagnosis and therapy to be effective,accurate,and reliable.Gene expression ... Lung cancer is among the most frequent cancers in the world,with over one million deaths per year.Classification is required for lung cancer diagnosis and therapy to be effective,accurate,and reliable.Gene expression microarrays have made it possible to find genetic biomarkers for cancer diagnosis and prediction in a high-throughput manner.Machine Learning(ML)has been widely used to diagnose and classify lung cancer where the performance of ML methods is evaluated to identify the appropriate technique.Identifying and selecting the gene expression patterns can help in lung cancer diagnoses and classification.Normally,microarrays include several genes and may cause confusion or false prediction.Therefore,the Arithmetic Optimization Algorithm(AOA)is used to identify the optimal gene subset to reduce the number of selected genes.Which can allow the classifiers to yield the best performance for lung cancer classification.In addition,we proposed a modified version of AOA which can work effectively on the high dimensional dataset.In the modified AOA,the features are ranked by their weights and are used to initialize the AOA population.The exploitation process of AOA is then enhanced by developing a local search algorithm based on two neighborhood strategies.Finally,the efficiency of the proposed methods was evaluated on gene expression datasets related to Lung cancer using stratified 4-fold cross-validation.The method’s efficacy in selecting the optimal gene subset is underscored by its ability to maintain feature proportions between 10%to 25%.Moreover,the approach significantly enhances lung cancer prediction accuracy.For instance,Lung_Harvard1 achieved an accuracy of 97.5%,Lung_Harvard2 and Lung_Michigan datasets both achieved 100%,Lung_Adenocarcinoma obtained an accuracy of 88.2%,and Lung_Ontario achieved an accuracy of 87.5%.In conclusion,the results indicate the potential promise of the proposed modified AOA approach in classifying microarray cancer data. 展开更多
关键词 Lung cancer gene selection improved arithmetic optimization algorithm and machine learning
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A multi-scale second-order autoregressive recursive filter approach for the sea ice concentration analysis
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作者 Lu Yang Xuefeng Zhang 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2024年第3期115-126,共12页
To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregress... To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregressive filter used in this study has been attempted to replace the traditional first-order recursive filter used in spatial multi-scale recursive filter(SMRF)method.The experimental results indicate that the MSRF scheme successfully extracts various scale information resolved by observations.Moreover,compared with the SMRF scheme,the MSRF scheme improves computational accuracy and efficiency to some extent.The MSRF scheme can not only propagate to a longer distance without the attenuation of innovation,but also reduce the mean absolute deviation between the reconstructed sea ice concentration results and observations reduced by about 3.2%compared to the SMRF scheme.On the other hand,compared with traditional first-order recursive filters using in the SMRF scheme that multiple filters are executed,the MSRF scheme only needs to perform two filter processes in one iteration,greatly improving filtering efficiency.In the two-dimensional experiment of sea ice concentration,the calculation time of the MSRF scheme is only 1/7 of that of SMRF scheme.This means that the MSRF scheme can achieve better performance with less computational cost,which is of great significance for further application in real-time ocean or sea ice data assimilation systems in the future. 展开更多
关键词 second-order auto-regressive filter multi-scale recursive filter sea ice concentration three-dimensional variational data assimilation
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An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic
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作者 Yan Zhang Bowen Du +3 位作者 Benren Pan GuannanWang Guoqiang Xie Tong Jiang 《Energy Engineering》 EI 2024年第7期1903-1920,共18页
During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in unc... During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems. 展开更多
关键词 Short circuit calculation inverter type distributed power supplies affine arithmetic distribution network
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Enhanced Arithmetic Optimization Algorithm Guided by a Local Search for the Feature Selection Problem
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作者 Sana Jawarneh 《Intelligent Automation & Soft Computing》 2024年第3期511-525,共15页
High-dimensional datasets present significant challenges for classification tasks.Dimensionality reduction,a crucial aspect of data preprocessing,has gained substantial attention due to its ability to improve classifi... High-dimensional datasets present significant challenges for classification tasks.Dimensionality reduction,a crucial aspect of data preprocessing,has gained substantial attention due to its ability to improve classification per-formance.However,identifying the optimal features within high-dimensional datasets remains a computationally demanding task,necessitating the use of efficient algorithms.This paper introduces the Arithmetic Optimization Algorithm(AOA),a novel approach for finding the optimal feature subset.AOA is specifically modified to address feature selection problems based on a transfer function.Additionally,two enhancements are incorporated into the AOA algorithm to overcome limitations such as limited precision,slow convergence,and susceptibility to local optima.The first enhancement proposes a new method for selecting solutions to be improved during the search process.This method effectively improves the original algorithm’s accuracy and convergence speed.The second enhancement introduces a local search with neighborhood strategies(AOA_NBH)during the AOA exploitation phase.AOA_NBH explores the vast search space,aiding the algorithm in escaping local optima.Our results demonstrate that incorporating neighborhood methods enhances the output and achieves significant improvement over state-of-the-art methods. 展开更多
关键词 arithmetic optimization algorithm CLASSIFICATION feature selection problem optimization
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Non-Recursive Base Conversion Using a Deterministic Markov Process
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作者 Louis M. Houston 《Journal of Applied Mathematics and Physics》 2024年第6期2112-2118,共7页
We prove that non-recursive base conversion can always be implemented by using a deterministic Markov process. Our paper discusses the pros and cons of recursive and non-recursive methods, in general. And we include a... We prove that non-recursive base conversion can always be implemented by using a deterministic Markov process. Our paper discusses the pros and cons of recursive and non-recursive methods, in general. And we include a comparison between non-recursion and a deterministic Markov process, proving that the Markov process is twice as efficient. 展开更多
关键词 Base Conversion RECURSION Euclidean Division Geometric Series Markov Process
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Improved Arithmetic Optimization Algorithm with Multi-Strategy Fusion Mechanism and Its Application in Engineering Design
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作者 Yu Liu Minge Chen +3 位作者 Ran Yin Jianwei Li Yafei Zhao Xiaohua Zhang 《Journal of Applied Mathematics and Physics》 2024年第6期2212-2253,共42页
This article addresses the issues of falling into local optima and insufficient exploration capability in the Arithmetic Optimization Algorithm (AOA), proposing an improved Arithmetic Optimization Algorithm with a mul... This article addresses the issues of falling into local optima and insufficient exploration capability in the Arithmetic Optimization Algorithm (AOA), proposing an improved Arithmetic Optimization Algorithm with a multi-strategy mechanism (BSFAOA). This algorithm introduces three strategies within the standard AOA framework: an adaptive balance factor SMOA based on sine functions, a search strategy combining Spiral Search and Brownian Motion, and a hybrid perturbation strategy based on Whale Fall Mechanism and Polynomial Differential Learning. The BSFAOA algorithm is analyzed in depth on the well-known 23 benchmark functions, CEC2019 test functions, and four real optimization problems. The experimental results demonstrate that the BSFAOA algorithm can better balance the exploration and exploitation capabilities, significantly enhancing the stability, convergence mode, and search efficiency of the AOA algorithm. 展开更多
关键词 arithmetic Optimization Algorithm Adaptive Balance Factor Spiral Search Brownian Motion Whale Fall Mechanism
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Probability Distribution of Arithmetic Average of China Aviation Network Edge Vertices Nearest Neighbor Average Degree Value and Its Evolutionary Trace Based on Complex Network
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作者 Cheng Xiangjun Yang Fang Xiong Zhihua 《Journal of Traffic and Transportation Engineering》 2024年第4期163-174,共12页
In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average... In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace. 展开更多
关键词 Complex network China aviation network arithmetic average of edge vertices nearest neighbor average degree value linear evolution trace
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On the Equality of Weighted BajratarevićMeans to Quasi-Arithmetic Means
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作者 Yaxun Yang 《Journal of Applied Mathematics and Physics》 2024年第4期1126-1133,共8页
In this paper, we considered the equality problem of weighted Bajraktarević means with weighted quasi-arithmetic means. Using the method of substituting for functions, we first transform the equality problem into solv... In this paper, we considered the equality problem of weighted Bajraktarević means with weighted quasi-arithmetic means. Using the method of substituting for functions, we first transform the equality problem into solving an equivalent functional equation. We obtain the necessary and sufficient conditions for the equality equation. 展开更多
关键词 Bajraktarević Means Quasi-arithmetic Means Equality Problem Functional Equation
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Calculation connectivity reliability of road networks based on recursive decomposition arithmetic 被引量:2
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作者 潘艳荣 邓卫 《Journal of Southeast University(English Edition)》 EI CAS 2008年第1期85-89,共5页
In order to decrease the calculation complexity of connectivity reliability of road networks, an improved recursive decomposition arithmetic is proposed. First, the basic theory of recursive decomposition arithmetic i... In order to decrease the calculation complexity of connectivity reliability of road networks, an improved recursive decomposition arithmetic is proposed. First, the basic theory of recursive decomposition arithmetic is reviewed. Then the characteristics of road networks, which are different from general networks, are analyzed. Under this condition, an improved recursive decomposition arithmetic is put forward which fits road networks better. Furthermore, detailed calculation steps are presented which are convenient for the computer, and the advantage of the approximate arithmetic is analyzed based on this improved arithmetic. This improved recursive decomposition arithmetic directly produces disjoint minipaths and avoids the non-polynomial increasing problems. And because the characteristics of road networks are considered, this arithmetic is greatly simplified. Finally, an example is given to prove its validity. 展开更多
关键词 recursive decomposition arithmetic road network connectivity reliability disjoint minipath topological structure
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Recursive recurrent neural network:A novel model for manipulator control with different levels of physical constraints 被引量:3
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作者 Zhan Li Shuai Li 《CAAI Transactions on Intelligence Technology》 SCIE EI 2023年第3期622-634,共13页
Manipulators actuate joints to let end effectors to perform precise path tracking tasks.Recurrent neural network which is described by dynamic models with parallel processing capability,is a powerful tool for kinemati... Manipulators actuate joints to let end effectors to perform precise path tracking tasks.Recurrent neural network which is described by dynamic models with parallel processing capability,is a powerful tool for kinematic control of manipulators.Due to physical limitations and actuation saturation of manipulator joints,the involvement of joint constraints for kinematic control of manipulators is essential and critical.However,current existing manipulator control methods based on recurrent neural networks mainly handle with limited levels of joint angular constraints,and to the best of our knowledge,methods for kinematic control of manipulators with higher order joint constraints based on recurrent neural networks are not yet reported.In this study,for the first time,a novel recursive recurrent network model is proposed to solve the kinematic control issue for manipulators with different levels of physical constraints,and the proposed recursive recurrent neural network can be formulated as a new manifold system to ensure control solution within all of the joint constraints in different orders.The theoretical analysis shows the stability and the purposed recursive recurrent neural network and its convergence to solution.Simulation results further demonstrate the effectiveness of the proposed method in end‐effector path tracking control under different levels of joint constraints based on the Kuka manipulator system.Comparisons with other methods such as the pseudoinverse‐based method and conventional recurrent neural network method substantiate the superiority of the proposed method. 展开更多
关键词 dynamic neural networks recursive computation robotic manipulator
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Solving Arithmetic Word Problems of Entailing Deep Implicit Relations by Qualia Syntax-Semantic Model
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作者 Hao Meng Xinguo Yu +3 位作者 Bin He Litian Huang Liang Xue Zongyou Qiu 《Computers, Materials & Continua》 SCIE EI 2023年第10期541-555,共15页
Solving arithmetic word problems that entail deep implicit relations is still a challenging problem.However,significant progress has been made in solving Arithmetic Word Problems(AWP)over the past six decades.This pap... Solving arithmetic word problems that entail deep implicit relations is still a challenging problem.However,significant progress has been made in solving Arithmetic Word Problems(AWP)over the past six decades.This paper proposes to discover deep implicit relations by qualia inference to solve Arithmetic Word Problems entailing Deep Implicit Relations(DIR-AWP),such as entailing commonsense or subject-domain knowledge involved in the problem-solving process.This paper proposes to take three steps to solve DIR-AWPs,in which the first three steps are used to conduct the qualia inference process.The first step uses the prepared set of qualia-quantity models to identify qualia scenes from the explicit relations extracted by the Syntax-Semantic(S2)method from the given problem.The second step adds missing entities and deep implicit relations in order using the identified qualia scenes and the qualia-quantity models,respectively.The third step distills the relations for solving the given problem by pruning the spare branches of the qualia dependency graph of all the acquired relations.The research contributes to the field by presenting a comprehensive approach combining explicit and implicit knowledge to enhance reasoning abilities.The experimental results on Math23K demonstrate hat the proposed algorithm is superior to the baseline algorithms in solving AWPs requiring deep implicit relations. 展开更多
关键词 arithmetic word problem implicit quantity relations qualia syntax-semantic model
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Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol
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作者 Manar Ahmed Hamza Haya Mesfer Alshahrani +5 位作者 Sami Dhahbi Mohamed K Nour Mesfer Al Duhayyim ElSayed M.Tag El Din Ishfaq Yaseen Abdelwahed Motwakel 《Computer Systems Science & Engineering》 SCIE EI 2023年第5期1759-1773,共15页
Wireless Sensor Networks(WSN)has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of applications.In spite of this,it is chall... Wireless Sensor Networks(WSN)has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of applications.In spite of this,it is challenging to design energy-efficient WSN.The routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of network.In order to solve the restricted energy problem,it is essential to reduce the energy utilization of data,transmitted from the routing protocol and improve network development.In this background,the current study proposes a novel Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-hop Routing Protocol(DEAOA-MHRP)for WSN.The aim of the proposed DEAOA-MHRP model is select the optimal routes to reach the destination in WSN.To accomplish this,DEAOA-MHRP model initially integrates the concepts of Different Evolution(DE)and Arithmetic Optimization Algorithms(AOA)to improve convergence rate and solution quality.Besides,the inclusion of DE in traditional AOA helps in overcoming local optima problems.In addition,the proposed DEAOA-MRP technique derives a fitness function comprising two input variables such as residual energy and distance.In order to ensure the energy efficient performance of DEAOA-MHRP model,a detailed comparative study was conducted and the results established its superior performance over recent approaches. 展开更多
关键词 Wireless sensor network ROUTING multihop communication arithmetic optimization algorithm fitness function
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Fin Field Effect Transistor with Active 4-Bit Arithmetic Operations in 22 nm Technology
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作者 S.Senthilmurugan K.Gunaseelan 《Intelligent Automation & Soft Computing》 SCIE 2023年第2期1323-1336,共14页
A design of a high-speed multi-core processor with compact size is a trending approach in the Integrated Circuits(ICs)fabrication industries.Because whenever device size comes down into narrow,designers facing many po... A design of a high-speed multi-core processor with compact size is a trending approach in the Integrated Circuits(ICs)fabrication industries.Because whenever device size comes down into narrow,designers facing many power den-sity issues should be reduced by scaling threshold voltage and supply voltage.Initially,Complementary Metal Oxide Semiconductor(CMOS)technology sup-ports power saving up to 32 nm gate length,but further scaling causes short severe channel effects such as threshold voltage swing,mobility degradation,and more leakage power(less than 32)at gate length.Hence,it directly affects the arithmetic logic unit(ALU),which suffers a significant power density of the scaled multi-core architecture.Therefore,it losses reliability features to get overheating and increased temperature.This paper presents a novel power mini-mization technique for active 4-bit ALU operations using Fin Field Effect Tran-sistor(FinFET)at 22 nm technology.Based on this,a diode is directly connected to the load transistor,and it is active only at the saturation region as a function.Thereby,the access transistor can cutoff of the leakage current,and sleep transis-tors control theflow of leakage current corresponding to each instant ALU opera-tion.The combination of transistors(access and sleep)reduces the leakage current from micro to nano-ampere.Further,the power minimization is achieved by con-necting the number of transistors(6T and 10T)of the FinFET structure to ALU with 22 nm technology.For simulation concerns,a Tanner(T-Spice)with 22 nm technology implements the proposed design,which reduces threshold vol-tage swing,supply power,leakage current,gate length delay,etc.As a result,it is quite suitable for the ALU architecture of a high-speed multi-core processor. 展开更多
关键词 FinFET(22 nm)technology diode connection arithmetic logic unit reduce threshold voltage swing gate length delay leakage power
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Application of Recursive Query on Structured Query Language Server
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作者 荀雪莲 ABHIJIT Sen 姚志强 《Journal of Donghua University(English Edition)》 CAS 2023年第1期68-73,共6页
The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done correctly.Structured query language(SQL)is a database language and is used to manipulate data... The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done correctly.Structured query language(SQL)is a database language and is used to manipulate data.In Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its disadvantages.Common table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive CTE.Hierarchical data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive CTEs.The recursive query is illustrated and implemented on some simple hierarchical data.In addition,one business case study is brought forward and the solution using recursive query based on CTE is shown.At the same time,stored procedures are programmed to do the recursion in SQL.Test results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax. 展开更多
关键词 structured query language(SQL)server common table expression(CTE) recursive query stored procedure hierarchical data
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Arithmetic Operations of Generalized Trapezoidal Picture Fuzzy Numbers by Vertex Method
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作者 Mohammad Kamrul Hasan Abeda Sultana Nirmal Kanti Mitra 《American Journal of Computational Mathematics》 2023年第1期99-121,共23页
In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis... In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis. Various related properties are explored. Finally, some computations of picture fuzzy functions over generalized picture fuzzy variables are illustrated by using our proposed technique. 展开更多
关键词 Picture Fuzzy Set Generalized Trapezoidal Picture Fuzzy Number γ β)-Cut arithmetic Operations Vertex Method
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溯源弹簧形变过程的断路器振动信号递归量化分析辨识方法 被引量:2
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作者 刘会兰 常庚垚 +2 位作者 赵书涛 付磊 刘教民 《电工技术学报》 EI CSCD 北大核心 2024年第8期2567-2577,共11页
从锁止机构脱扣引起储能弹簧释能,经部件带动动触头运动再到静止的每个动作具有严格阶段特征,伴随断路器动作的机械振动展现了能量传递及设备健康状态。该文提出一种溯源弹簧形变过程的断路器振动信号递归量化分析方法,首先由高速相机... 从锁止机构脱扣引起储能弹簧释能,经部件带动动触头运动再到静止的每个动作具有严格阶段特征,伴随断路器动作的机械振动展现了能量传递及设备健康状态。该文提出一种溯源弹簧形变过程的断路器振动信号递归量化分析方法,首先由高速相机捕捉断路器操动时储能弹簧的动作图像,通过计算机视觉跟踪动态提取反映弹簧形变特征帧,再依据特征帧时序划分操动过程;然后将不同阶段振动信号映射至高维相空间,经递归分析得到体现动力系统变化特征的递归图,并递归量化分析其纹理结构特征;最后利用支持向量机模型对正常及故障状态下的断路器振动特征样本进行分析辨识,对比结果证明,由弹簧释能时序细化振动信号特征分析有效提高了分类识别准确率。该文方法在断路器操动机构状态辨识中具有广阔的应用前景。 展开更多
关键词 高压断路器 动作阶段 振动信号 递归量化分析 状态辨识
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数据、算力和算法结合反映新质生产力的数字化发展水准 被引量:9
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作者 任保平 豆渊博 《浙江工商大学学报》 CSSCI 北大核心 2024年第3期91-100,共10页
数字经济的发展促进新的劳动主体、新的生产工具和新的生产要素不断涌现,为人们认识世界和改造世界创造了新模式,新质生产力的数字化发展是新质生产力在数字经济领域的表现。数字经济时代,数据作为新质生产力数字化发展的新要素,算力体... 数字经济的发展促进新的劳动主体、新的生产工具和新的生产要素不断涌现,为人们认识世界和改造世界创造了新模式,新质生产力的数字化发展是新质生产力在数字经济领域的表现。数字经济时代,数据作为新质生产力数字化发展的新要素,算力体现新质生产力数字化发展的新动能,算法反映新质生产力数字化发展的新优势,数据、算力和算法的结合反映了新质生产力的数字化发展水准,形成数字时代的新质生产力。新发展阶段,数据、算力和算法的结合首先引起生产力的决策革命,其次引起生产力的工具革命、劳动力革命、生产要素革命和技术—经济范式革命,进一步推动新质生产力的数字化发展。在全球经济新周期的背景下,提高新质生产力的数字化发展水平已经成为推动经济社会高质量发展的关键力量。 展开更多
关键词 新质生产力 数据+算力+算法 数字技术 智能化工具
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滤波辨识(10):多变量Box-Jenkins系统的滤波辅助模型递阶广义增广参数辨识 被引量:4
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作者 丁锋 万立娟 +2 位作者 栾小丽 徐玲 刘喜梅 《青岛科技大学学报(自然科学版)》 CAS 2024年第1期1-14,共14页
针对多变量Box-Jenkins模型,即多变量输出误差自回归滑动平均(M-OEARMA)系统,利用滤波辨识理念和辅助模型辨识思想,研究和提出了滤波辅助模型递阶广义增广随机梯度辨识方法、滤波辅助模型递阶多新息广义增广随机梯度辨识方法、滤波辅助... 针对多变量Box-Jenkins模型,即多变量输出误差自回归滑动平均(M-OEARMA)系统,利用滤波辨识理念和辅助模型辨识思想,研究和提出了滤波辅助模型递阶广义增广随机梯度辨识方法、滤波辅助模型递阶多新息广义增广随机梯度辨识方法、滤波辅助模型递阶广义增广递推梯度辨识方法、滤波辅助模型递阶多新息广义增广递推梯度辨识方法、滤波辅助模型递阶广义增广最小二乘辨识方法、滤波辅助模型递阶多新息广义增广最小二乘辨识方法。这些滤波辅助模型递阶广义增广辨识方法可以推广到其他有色噪声干扰下的线性和非线性多变量随机系统中。 展开更多
关键词 参数估计 递推辨识 辅助模型辨识 多新息辨识 递阶辨识 滤波辨识 最小二乘 多变量系统
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基于改进仿射算法的主动配电网区间调度 被引量:1
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作者 程杉 左先旺 +2 位作者 杨堃 傅桐 王灿 《电力自动化设备》 EI CSCD 北大核心 2024年第1期40-48,共9页
针对高渗透率分布式可再生能源的不确定性和仿射算法结果的保守性影响调度计划的问题,提出基于改进仿射算法的主动配电网区间优化调度模型及其求解方法。以区间变量表征分布式可再生能源中风机和光伏出力的不确定性,利用带有误差修正机... 针对高渗透率分布式可再生能源的不确定性和仿射算法结果的保守性影响调度计划的问题,提出基于改进仿射算法的主动配电网区间优化调度模型及其求解方法。以区间变量表征分布式可再生能源中风机和光伏出力的不确定性,利用带有误差修正机制的灰色马尔可夫模型得到风机和光伏出力的区间预测值。建立综合考虑主动配电网运行约束和灵活性指标,以综合运行费用最低和净负荷波动最小为目标的主动配电网多目标区间优化调度数学模型。在仿射算法的非线性运算中引入区间泰勒公式,提出一种改进仿射算法并将其应用于主动配电网潮流计算,并通过CPLEX和INTLAB对调度模型进行联合求解。修改的IEEE 33节点系统的仿真结果表明,区间优化调度可为调度人员提供更直观的主动配电网状态量上、下界信息,而且所提方法的计算效率更高,所得区间结果的保守性、可靠性和有效性更优。 展开更多
关键词 不确定性 改进仿射算法 保守性 区间优化调度 潮流计算
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基于多阶段递推数据分析的低压台区窃电检测方法 被引量:1
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作者 孔祥玉 马玉莹 +1 位作者 赵鑫 梁博浩 《中国电机工程学报》 EI CSCD 北大核心 2024年第15期5921-5933,I0007,共14页
窃电行为不仅会扰乱正常用电秩序,更会影响电网的供电质量和安全运行。针对窃电检测工作中所面临的用户正常用电行为与窃电行为多样化问题,该文提出一种基于多阶段递推数据分析的低压台区窃电检测方法。该方法第1阶段对嫌疑窃电台区进... 窃电行为不仅会扰乱正常用电秩序,更会影响电网的供电质量和安全运行。针对窃电检测工作中所面临的用户正常用电行为与窃电行为多样化问题,该文提出一种基于多阶段递推数据分析的低压台区窃电检测方法。该方法第1阶段对嫌疑窃电台区进行判定,针对当日线损不是明显激增的情况,提出基于台区线损综合波动率、总分表电流差异率、线损和电流曲线的突变点时间重合度的三步分析法,为窃电嫌疑用户的检测提供了良好的条件;第2阶段提出基于最优特征集的时间序列相似性度量方法,基于欧氏距离度量曲线间数值特征,同时基于动态时间规整(dynamic time warping,DTW)算法度量曲线间的形态特征,实现窃电嫌疑用户的初步筛选;第3阶段提出基于核函数和惩罚参数优化的支持向量机二次深度检测模型(optimize kernel-function and penalty-parameters support vector machine,OKPSVM),其中惩罚参数采用综合改进的粒子群(improved particle swarm optimization,IPSO)算法。通过算例仿真和实际工程应用,整体优化后的支持向量机模型(IPSO-OKPSVM)能够提高深度窃电检测的精准性和适用性。 展开更多
关键词 低压台区 窃电检测 多阶段递推 特征相似性度量 支持向量机
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