检索结果-内蒙古大学图书馆

TMHSCA: a novel hybrid two-stage mutation with a sine cosine algorithm for discounted {0-1} knapsack problems

NEURAL COMPUTING & APPLICATIONS 2023年第17期35卷 12691-12713页

作者： Kang, Yan Wang, Haining Pu, Bin Liu, Jiansong Lee, Shin-Jye Yang, Xuekun Tao, Liu Yunnan Univ Sch Software Kunming 650500 Yunnan Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Hunan Peoples R China Natl Yang Ming Chiao Tung Univ Inst Management Technol 1001 Univ Rd Hsinchu 30010 Taiwan

The discounted {0-1} knapsack problem (DKP) is an NP-hard problem that is more challenging than the classical knapsack problem. In this paper, an enhanced version of the sine-cosine algorithm (SCA) called TMHSCA is proposed to solve the DKP. The SCA is a novel metaheuristic algorithm based on sine-cosine theory. Three effective improvements are proposed for the SCA to enhance the convergence speed and exploitation capability of the algorithm. First, by dividing the initial population into three subpopulations using random, greedy and opposition-based learning (OBL) strategies, the diversity of the population can be effectively enhanced. Furthermore, a forward-inverse sine-cosine search that expands the search space by utilizing the worst solution as another target is proposed. The proposed forward-inverse sine-cosine search strategy facilitates the algorithm to explore the easily ignored solution space. The last improvement includes the use of an OBL mutation and the mutation operator of differential evolution at a two-stage mutation, which increases the algorithm's convergence speed and fitness. In our proposed two-stage mutation, the number of mutations can be adaptively adjusted based on the optimization capabilities of the optimal individual. Additionally, a reshuffling repair strategy for repairing infeasible solutions by sorting items into groups to obtain the weight-to-value ratio is proposed. Extensive experiments are conducted on 40 publicly available datasets and are compared to the greedy algorithm, 3 SCAs and 8 competitive baseline methods. The experimental results demonstrate that our method achieves a state-of-the-art performance.

关键词： Discounted {0-1} knapsack problem sine-cosine algorithm Opposition-based learning theory Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

Revamped sine cosine algorithm Centered Optimization of System Stabilizers and Oscillation Dampers for Wind Penetrated Power System

引用

IEEE ACCESS 2023年 11卷 1890-1905页

作者： Sadhana, S. Grace Kumaravel, S. Ashok, S. Natl Inst Technol Calicut Dept Elect Engn Calicut 673601 Kerala India

The mapping of damping ratios and damping factors by sine-cosine algorithm (SCA) is significant in the analysis of low frequency oscillations generated in an integrated network having multiple conventional and renewable energy sources. Multiple random models with unknown search spaces and uncertain conditions and constraints, which incorporate the fluctuation of solutions towards or outwards at the initial stage for solving real-time problems can be analyzed by a revamped sine-cosine algorithm (RSCA) model. In this paper, the SCA has been revamped to explore the stability threshold for a stable system under dynamic nonlinear operating conditions. It is achieved with the infusion of suitable mathematical functions for optimizing the parameters of Power System Stabilizers (PSSs) and Doubly Fed Induction Generator (DFIG) system-based oscillation dampers to enhance the Small Signal Stability of power systems through effective damping of low-frequency oscillations (LFOs). These LFOs weaken the effective power generation and demand management cycle in conventional power systems when the system faces conditions like intermittent renewable energy sources, overloading conditions, impulsive faults etc. The small-signal and transient stability studies for various disturbances and different operating conditions are investigated, and the performance of the proposed RSCA for optimized parameter tuning of system stabilizers and oscillation dampers are analyzed on the modified benchmarking systems with wind generators using MATLAB CIRCLED LATIN CAPITAL LETTER R simulations. The efficiency and robustness of the proposed algorithm has been verified under selective critical operating conditions, line outages, and load uncertainties to prove that the low frequency modes are damped with an elevated positive damping ratio and rapid settling time with reduced oscillations. The application of system stabilizers and oscillation dampers optimized through the proposed RSCA shows a reduced set

关键词： Power system stability Damping Oscillators Optimization Wind power generation Tuning Shock absorbers Low-frequency oscillations optimization problem power system stabilizer (PSSs) power oscillation dampers (PODs) sine-cosine algorithm wind energy conversion systems (WECS)

来源：评论

学校读者我要写书评

暂无评论

A hybrid k-prototypes clustering approach with improved sine-cosine algorithm for mixed-data classification

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2022年 169卷

作者： Kuo, Timothy Wang, Kung-Jeng Penn State Univ Dept Ind & Mfg Engn University Pk PA 16802 USA Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei 106 Taiwan

When dealing a classification problem with mixed data, most of conventional supervised learning algorithms cannot perform well due to their numerical characteristics. However, some clustering algorithms, such as k- prototypes algorithm, show their potential in clustering mixed data. Therefore, the current study intends to develop a novel clustering-based classification algorithm for mixed data to have both merits of classification and clustering. The proposed algorithm employs a sine-cosine algorithm (SCA) to find attribute weights and initial centroids for a k-prototypes algorithm. The objective function of the algorithm is formulated as a sum-up purity. To have better performance for SCA, a mutation strategy, containing Gaussian mutation, Cauchy mutation, Levy mutation, and single-point mutation, is embedded into the original SCA. The proposed algorithm is compared with some metaheuristic-based classification algorithms and existing classification algorithms. Based on the 10 data sets from UCI, the experimental results indicated that the proposed algorithm can achieve superior clas-sification performance in terms of accuracy and Cohen's Kappa. In addition, mutation mechanism can make SCA have better performance

关键词： Classification Clustering Clustering-based classification Mixed data Genetic algorithm sine-cosine algorithm Mutation

来源：评论

学校读者我要写书评

暂无评论

Multi-agent based sine-cosine algorithm for optimal integration of DERs with consideration of existing OLTC in distribution networks

引用

APPLIED SOFT COMPUTING 2022年第0期117卷 108387-108387页

作者： Patel, C. D. Tailor, T. K. Nirma Univ Inst Technol Dept Elect Engn Ahmadabad Gujarat India

In this work, a modified version of the sine-cosine algorithm (SCA) has been developed to solve complex optimization problems. This proposed modified algorithm integrates the multi-agent system and sine-cosine algorithm and is termed as multi-agent sine-cosine algorithm (MA-SCA). This work also proposes a simplified strategy for the self-learning operator and modification in inversion operator. These proposed modifications have been validated by implementing the proposed MA-SCA algorithm on standard functions and comparing results with other reported optimization methods. Furthermore, in this work, MA-SCA algorithm has also been applied to optimally deploy the distributed energy resources (DERs) and shunt capacitors (SCs) in the distribution network with and without consideration of the existing on-load tap changing transformer (OLTC). The considered objectives in this optimization problem are reduction of cost of annual energy loss (CAEL) and minimization of voltage deviation under different loading conditions. To demonstrate the efficacy of the MA-SCA algorithm, it has been implemented on IEEE 33 bus radial distribution network (DN) and real-life Indian 108 bus radial DN. The comparison of obtained results with the results obtained by using other optimization methods has been carried out, and it indicates that MA-SCA algorithm provides the improved solution. (C) 2021 Elsevier B.V. All rights reserved.

关键词： sine-cosine algorithm Multi-agent system Distributed energy resources On-load tap changing transformer

来源：评论

学校读者我要写书评

暂无评论

Urban traffic light scheduling for pedestrian-vehicle mixed-flow networks using discrete sine-cosine algorithm and its variants

引用

APPLIED SOFT COMPUTING 2022年第0期120卷 108656-108656页

作者： Gupta, Shubham Zhang, Yi Su, Rong Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Inst Infocomm Res Agcy Sci Technol & Res A STAR Singapore Singapore

This study addresses the traffic light scheduling problem for pedestrian-vehicle mixed-flow networks. A macroscopic model, which strikes an appropriate balance between pedestrians' needs and vehicle drivers' needs, is employed to describe the traffic light scheduling problem in a scheduling framework. The objective of this problem is to minimize the total network-wise delay time of vehicles and pedestrians within a given finite-time window, which is crucial to avoid traffic congestion in urban road networks. To achieve this objective, the present study first uses a well-known optimization solver called GUROBI to obtain the optimal solution by converting the problem into mixed-integer linear programming. The obtained results indicate the computational inefficiency of the solver for large network sizes. To overcome this computational inefficiency, three novel metaheuristic methods based on the sine-cosine algorithm are proposed. These methods are denoted by discrete sine- cosine algorithm, discrete sine-cosine algorithm with local search operator, and discrete sine-cosine algorithm with local search operator and memory utilization inspired by harmony search. Each of these methods is developed hierarchically by taking the advantages of previously developed method(s) in terms of a better search process to provide more accurate solutions and a better convergence rate. To validate all these proposed metaheuristics, extensive computational experiments are carried out using the real traffic infrastructure of Singapore. Moreover, various performance measures such as statistical optimization results, relative percentage deviation, computational time, statistical analysis, and convergence behavior analysis have been employed to evaluate the performance of algorithms. The comparison of the proposed SCA variants is done with GUROBI solver and other metaheuristics namely, harmony search, firefly algorithm, bat algorithm, artificial bee colony, genetic algorithm, salp swarm algori

关键词： Traffic light scheduling Vehicle flow model Pedestrian flow model Metaheuristics sine-cosine algorithm

来源：评论

学校读者我要写书评

暂无评论

A new algorithm to generate aes-like substitution boxes based on sine cosine optimization algorithm

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2023年第13期83卷 38949页

作者： Artuger, Firat Ozkaynak, Fatih Munzur Univ Dept Comp Engn TR-62200 Tunceli Turkiye Fırat Univ Dept Software Engn TR-23119 Elazig Turkiye

Symmetric encryption approaches are generally used for data encryption. One of the basic requirements for symmetric encryption algorithms to provide security is strong s-box structures. Because s-box is a nonlinear unit in these encryption algorithms and provides the requirement called confusion. In this article, a new technique is developed to produce effective s-boxes like the 16*16 s-box structure used in the AES algorithm. In the proposed method, the sine cosine algorithm (SCA), one of the recently developed optimization algorithms, is used. SCA is a suitable option for generating strong s-boxes because of its strong randomness and ease of implementation. The proposed method first uses a logistic map to generate the initial population. Then, the nonlinearity value is optimized with the help of the sine cosine algorithm. The proposed method reaches the highest nonlinearity value (112) by relocating 126 values in the s-box structure produced initially. Looking at the results, it is seen that the proposed method gives better results than other optimization-based s-box creation methods. This new method has significant potential to improve the security of symmetric encryption algorithms and make data encryption processes stronger.

关键词： Security S-box sine-cosine algorithm High nonlinearity AES Symmetric encryption

来源：评论

学校读者我要写书评

暂无评论

A Linearly Adaptive sine-cosine algorithm with Application in Deep Neural Network for Feature Optimization in Arrhythmia Classification using ECG Signals

引用

KNOWLEDGE-BASED SYSTEMS 2022年 242卷 108411-108411页

作者： Sharma, Pooja Dinkar, Shail Kumar Seth Jai Parkash Mukand Lal Inst Engn & Technol J Dept Informat Technol Radaur Haryana India Uttarakhand Tech Univ Dehra Dun Uttarakhand India GBPIET Dept Comp Sci & Applicat Pauri Garhwal Uttarakhand India

This work proposes a novel variant namely Linear Adaptive sine-cosine algorithm (LA-SCA) of newly developed metaheuristic called sine-cosine algorithm (SCA). The developed variant utilizes a linearly adaptive operator that is based on the number of generations, followed by an Opposition based Learning (OBL) model applied around the best solution. The applied mechanisms help LA-SCA to overcome the slow convergence problem in SCA and capable of achieving appropriate balance between macro and micro search ability of SCA. The performance of proposed LA-SCA is evaluated using a set of 23 state-of-the-art benchmark problems having a variety of characteristics and diverse complexities. The LA-SCA is statistically analysed by applying a Wilcoxon ranksum test and performance analysis using convergence curves and diversity analysis. In second part, the proposed LA-SCA is utilized to offer an intelligent Deep Neural Network (DNN) mechanism for improving the feature extraction of ECG signal for efficient classification of arrhythmia diseases. During the pre-processing step, Discrete Wavelet Transformation (DWT) is utilized to categorize ECG data followed by improving the extraction of QRS complex features using proposed LA-SCA. The MIT-BIH Arrhythmia ECG dataset is used in order to perform classification of signals among sixteen categories of arrhythmia disease. By using the classification analysis on the basis of variation including optimized feature vector and the LASCA method with DNN, the heart rate has been observed with an improved 99.29 percent accuracy as compared to other techniques. This achieved accuracy demonstrated the superiority of proposed model for appropriately classifying the ECG signal. (C) 2022 Elsevier B.V. All rights reserved.

关键词： sine-cosine algorithm Linear Adaptive operator Opposition based Learning Deep Neural Network (DNN) Electrocardiogram (ECG)

来源：评论

学校读者我要写书评

暂无评论

Diversified sine-cosine algorithm based on differential evolution for multidimensional knapsack problem

引用

APPLIED SOFT COMPUTING 2022年 130卷

作者： Gupta, Shubham Su, Rong Singh, Shitu Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore South Asian Univ Dept Math New Delhi 110021 India

The sine-cosine algorithm (SCA) is one of the simplest and efficient stochastic search algorithms in the field of metaheuristics. It has shown its efficacy in solving several real-life applications. However, in some cases, it shows stagnation at local optima and premature convergence issues due to low exploitation ability and insufficient diversity skills. To overcome these issues from the SCA, its enhanced version named ISCA is developed in this paper. The proposed ISCA is designed based on modifying the original search mechanism of the SCA and hybridizing it with a differential evolution (DE) algorithm. The search procedure in the ISCA switches between the modified search mechanism of the SCA and DE based on the evolutionary states of candidate solutions and a parameter called the switch parameter. The modified SCA enhances the exploitation ability and convergence speed, while the DE maintains the diversity of the population to avoid local optimal solutions. The parameters of the ISCA are tuned in such as way that they could balance the exploration and exploitation features. Validation of the ISCA is conducted on a benchmark set of 23 continuous optimization problems through different performance measures, which reveals its effectiveness as a better optimizer for continuous optimization problems. Furthermore, the proposed ISCA is extended to develop its efficient binary version named BISCA for solving multidimensional knapsack problems. A benchmark collection of 49 instances is used for the performance evaluation of the BISCA. Comparison of results produced by the BISCA with other algorithms and previous studies indicates its better search efficiency and verifies it as an effective alternative for solving the MKP.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Global optimization sine-cosine algorithm Differential evolution Binary optimization Multidimensional knapsack problem

来源：评论

学校读者我要写书评

暂无评论

Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine algorithm

引用

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2023年第SUPPL 1期14卷 307-327页

作者： Banerjee, Mousumi Garg, Vanita Deep, Kusum Galgotias Univ Sch Basic & Appl Sci Greater Noida India IIT Roorkee Dept Math Roorkee India

Many real-life complex problems are formulated as optimization problems. These mathematical equations generally are non-convex and non-linear functions. These problems are effectively solved using nature inspired algorithms. sine-cosine algorithm is one of the recent advancements in field of nature inspired optimization technique. Diversification and intensification are two components of a robust nature inspired algorithm. sine-cosine algorithm has potential to solve many real-life complex problems. However, lack of diversification ability of search space leads to investigation of different mutation strategies-Gaussian, Cauchy, Random, Polynomial, Power mutation on sine-cosine algorithm. The scope of this paper is of three folds. Firstly, to purpose a new algorithm embedded with five different mutation strategies. Secondly, to check the proposed version of algorithm on 23 benchmark problems of efficient difficulty/complexity level. Thirdly, to apply the proposed version of algorithms to solve real life problems of engineering and reliability problems.

关键词： sine-cosine algorithm Gaussian mutation Cauchy mutation Random mutation

来源：评论

学校读者我要写书评

暂无评论

Optimal economic-environmental dispatch in MT-HVDC systems via sine-cosine algorithm

引用

RESULTS IN ENGINEERING 2022年 13卷

作者： Montoya, Oscar Danilo Giral-Ramirez, Diego Armando Grisales-Norena, Luis Fernando Univ Dist Francisco Jose de Caldas Fac Ingn Bogota DC Colombia Univ Tecnol Bolivar Fac Ingn Lab Inteligente Energia Cartagena Colombia Univ Dist Francisco Jose de Caldas Fac Tecnol Bogota DC Colombia Inst Univ Pascual Bravo Fac Ingn Campus Robledo Medellin Colombia

This paper addresses the problem of optimal economic-environmental dispatch in Multi-Terminal High-Voltage Direct Current (MT-HVDC) networks using the sine-cosine algorithm (SCA). This optimization methodology allows working with nonlinear non-convex large-scale optimization problems via sequential programming. The SCA works with an initial population and rules of advance based on the best current solution and sine and cosine functions that define the direction of the next solution. Three variants of the SCA are evaluated in a standard six node MT-HVDC system considering a linear combination of the objective functions (i.e., greenhouse emissions and energy production costs). The main advantage of the proposed evolutionary approach lies in its pure algorithmic structure. Thus, it can be easily adapted to any continuous optimization problem. All numerical calculations are performed using MATLAB software.

关键词： Direct-current networks Economic-environmental dispatch problem Metaheuristic optimization sine-cosine algorithm Weighting factor method

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：