检索结果-内蒙古大学图书馆

A hybrid multi-objective algorithm based on slime mould algorithm and sine cosine algorithm for overlapping community detection in social networks

引用

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第10期27卷 13897-13917页

作者： Heydariyan, Ahmad Gharehchopogh, Farhad Soleimanian Dishabi, Mohammad Reza Ebrahimi Islamic Azad Univ Dept Comp Engn Miyaneh Branch Miyaneh Iran Islamic Azad Univ Dept Comp Engn Urmia Branch Orumiyeh Iran

In recent years, extensive studies have been carried out in community detection for social network analysis because it plays a crucial role in social network systems in today's world. However, most social networks in the real world have complex overlapping social structures, one of the NP-hard problems. This paper presents a new model for overlapping community detection that uses a multi-objective approach based on a hybrid optimization algorithm. In this model, the Modified Selection Function (MSF) hybrids the algorithms and recovery mechanism, the Slime Mould algorithm (SMA), the sine cosine algorithm (SCA), and the association strategy. Also, considering that these algorithms have been presented to solve single-objective optimization problems, the Pareto dominance technique has been used to solve multi-objective problems. In addition to overlapping community detection and increasing detection accuracy, the fuzzy clustering technique has been used to select the heads of clusters. Sixteen synthetic and real-world data sets were utilized to assess the suggested model, and the outcomes were contrasted with those of existing optimization techniques. The proposed model has performed better than the other tested algorithms in comparing the tests conducted by us in all 16 data sets, in the comparisons made with the algorithms proposed in other works in 11 data sets out of 14 data. The set has performed better than competitors. As a conclusion, the findings show that this model performs better than other methods.

关键词： Modified selection function Slime mould algorithm sine cosine algorithm Association strategy Fuzzy clustering Overlapping community detection

来源：评论

学校读者我要写书评

暂无评论

A parameter adaptive sine cosine algorithm for global optimization problems

ENGINEERING RESEARCH EXPRESS

引用

ENGINEERING RESEARCH EXPRESS 2025年第1期7卷

作者： Cheng, Jiatang Song, Peisen Xiong, Yan Guilin Univ Technol Educ Dept Guangxi Zhuang Autonomous Reg Key Lab Adv Mfg & Automat Technol Guilin 541006 Peoples R China Guilin Univ Technol Coll Mech & Control Engn Guilin 541006 Peoples R China

sine cosine algorithm (SCA) is a random search technique for global numerical optimization. However, SCA still exhibits low efficiency for some complex problems. In this paper, we develop a novel SCA variant (PASCA) by introducing a parameter adaptive mechanism. Specifically, the control parameter is produced based on a Cauchy distribution rather than the original linear decreasing scheme. After that, at the end of each generation, the successful historical information is utilized to dynamically update the control parameter, which helps to strengthen the search ability and reduce dependence on the problem to be solved. To verify the effectiveness of PASCA algorithm, comparison experiments are conducted on 43 benchmark functions including 13 classic problems and CEC 2017 test suite as well as a time series prediction problem. Simulation results demonstrate that PASCA is an efficient and promising optimization method compared with the classic SCA and its four recent strong variants.

关键词： sine cosine algorithm control parameter adaptive mechanism optimization

来源：评论

学校读者我要写书评

暂无评论

Development of Novel Hybrid Multi-Verse Optimizer with sine cosine algorithm for Better Global Optimization

引用

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS 2024年第2期23卷 2450002-2450002页

作者： Son, Pham Vu Hong Trinh, Nguyen Dang Nghiep Vietnam Natl Univ VNU HCM Ho Chi Minh City Univ Technol HCMUT Ho Chi Minh City Vietnam

The sine cosine algorithm (SCA) and multi-verse optimizer (MVO) are the recognized optimization strategies frequently employed in numerous scientific areas. However, both SCA and MVO grapple with optimizing the transition between the exploitation and exploration mechanisms. Furthermore, MVO exhibits constraints in its exploitation capabilities. To tackle these limitations, this paper introduces a hybrid model termed SMVO, combining the advantages of both SCA and MVO. This hybrid approach seeks to harmonize exploitation and exploration stages by leveraging the unique advantages of each parent algorithm. The efficacy of SMVO was assessed using 23 benchmark test functions, revealing its competitive performance against not only SCA and MVO but also the ant lion optimization (ALO) and the dragonfly algorithm (DA). Additionally, SMVO's applicability was further validated by successfully addressing three distinct engineering optimization challenges, underscoring its stability and promise as a global optimization tool.

关键词： Hybrid algorithm optimization problem sine cosine algorithm global optimization multi-verse optimizer

来源：评论

学校读者我要写书评

暂无评论

sine cosine algorithm for Solving Economic Load Dispatch Problem With Penetration of Renewables

引用

INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH 2022年第1期13卷 1-21页

作者： Verma, Diwakar Soni, Jatin Kalathia, Dhruv Bhattacharjee, Kuntal Nirma Univ Inst Technol Ahmadabad Gujarat India

Economic load dispatch is used to allocate power demand economically among connected generators by considering various constraints. The thermal generating units are incorporated with renewable sources like wind and solar units to reduce pollution and dependency on fuel cost. The uncertainty of output power from wind and solar plants is considered here. The 2-m point estimation method is used to get generated power from wind and solar units. The population-based sine cosine algorithm is proposed to get the optimum solution of the presented complex ELD problem. The randomly placed search agents find an optimum solution according to their fitness values and keep path towards best solution attained by each search agent. The search agents avoid local optima in exploration stage and move towards the solution exploitation stage using sine and cosine functions. The proposed algorithm has been tested in various four test systems. The results proved that the proposed algorithm gives quite an effective, efficient, and promising solution compared to other techniques.

关键词： 2-m Point Estimation Method Economic Load Dispatch Renewable Energy Sources sine cosine algorithm Valve Point Effect

来源：评论

学校读者我要写书评

暂无评论

An improved sine cosine algorithm with heterogeneous subpopulations for global optimization and fractional order PID controller design

引用

APPLIED INTELLIGENCE 2023年第15期53卷 18581-18604页

作者： Li, Qijun Ning, Huifeng Gong, Jun Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou 730050 Gansu Peoples R China Tianshui Nomal Univ Sch Electromech & Automobile Engn Tianshui 741000 Gansu Peoples R China

As one of recently proposed optimization algorithm, sine cosine algorithm (SCA) suffers from the problems of skipping over true solutions, stagnating in local optima and premature convergence. Therefore, an improved sine cosine algorithm with heterogeneous subpopulations (HSISCA) is developed in this paper. The population of HSISCA is divided into two subpopulations which comply with different search mechanisms and information sharing rules. One subpopulation is specified to enhance exploration by incorporating Levy flight and random search guidance into SCA, while the other is specified to enhance exploitation by adaptive differential mutation operator. The exploration subpopulation is denied access to the information of exploitation subpopulation, but the exploitation subpopulation is allowed access to the information of exploration subpopulation. Moreover, the greedy selection is applied to each individual to preserve useful information. HSISCA is tested on the CEC2014 and CEC2017 benchmark functions, and is used for designing fractional order PID (FOPID) controller. The results confirm the better performance of HSISCA compared to other competitive algorithms, and demonstrate the effectiveness of HSISCA in designing FOPID controller for complex systems.

关键词： Optimization sine cosine algorithm Subpopulation Differential mutation Controller design

来源：评论

学校读者我要写书评

暂无评论

Elite and dynamic opposite learning enhanced sine cosine algorithm for application to plat-fin heat exchangers design problem

引用

NEURAL COMPUTING & APPLICATIONS 2023年第17期35卷 12401-12414页

作者： Zhang, Lidong Hu, Tianyu Yang, Zhile Yang, Dongsheng Zhang, Jianhua Northeast Elect Power Univ Jilin 132012 Jilin Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Northeastern Univ Intelligent Elect Sci & Technol Res Inst Shenyang 110819 Peoples R China North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China

The heat exchanger has been widely used in the energy and chemical industry and plays an irreplaceable role in the featured applications. The design of heat exchanger is a mixed integer complex optimization problem, where the efficient design significantly improves the efficiency and reduces the cost. Many intelligent methods have been developed for heat exchanger optimal design. In this paper, a novel variant of sine and cosine algorithm named EDOLSCA is proposed, enhanced by dynamic opposite learning algorithm and the elite strategy. The proposed method is tested in CEC2014 benchmark and proved to be of significant advantages over the original algorithm. The new algorithm is then validated in the plate-fin heat exchanger (PFHE) optimal design problem. The comparison results of the proposed algorithm and other algorithms prove that EDOLSCA also has demonstrated superiority in heat exchanger optimal design.

关键词： Plate-fin heat exchanger Design optimization sine cosine algorithm Dynamic-opposite learning

来源：评论

学校读者我要写书评

暂无评论

Application of chaos assisted sine cosine algorithm on wind-solar integrated hydrothermal scheduling problem

引用

OPTIMAL CONTROL APPLICATIONS & METHODS 2023年第2期44卷 1026-1051页

作者： Dasgupta, Koustav Roy, Provas Kumar Mukherjee, V. Techno India Univ Dept Elect Engn Salt Lake West Bengal India Kalyani Govt Engn Coll Dept Elect Engn Kalyani West Bengal India Indian Sch Mines Indian Inst Technol Dept Elect Engn Dhanbad Jharkhand India

In recent times, renewable energy sources are essential for generating low-cost, pollution-free power. Since the last two decades, hydrothermal coordination system has been used to fulfill the demand power. The traditional generating model's two biggest flaws are high generation cost and excessive fossil fuel emission. In the proposed work, generation process of traditional hydrothermal scheduling (HTS) has been improved by integrating wind-solar energy. To overcome current issues of HTS, that is, excessive emission and generation cost, hydrothermal-solar-wind scheduling (HTSWS) problem has been introduced where two wind and two solar power generating units have been considered with four hydro and three thermal power generating units. Here, effective performance of low cost-emission based proposed HTSWS has been examined by using chaos-based sine cosine algorithm (SCA) (CSCA). Chaos has been used in sine cosine function of SCA to improve searching process for finding global optimal results. The proposed CSCA has been used to investigate three separate situations of standard HTS and recommended HTSWS problems including generation cost, emission, and combined cost-emission. The cost of generation and emissions from conventional HTS can be reduced by 11% and 68%, respectively, by the suggested renewable energy source-based generation model. The results of several case studies of proposed HTSWS and standard HTS reveal that wind-solar energy is effective in the HTS issue, and chaos assists in the SCA to improve its optimization process. In this study, effectiveness and robustness of the CSCA have been demonstrated by comparing the CSCA-based results to existing methods for the challenges under consideration.

关键词： chaos hydrothermal scheduling sine cosine algorithm solar energy wind energy

来源：评论

学校读者我要写书评

暂无评论

Triangular-based sine cosine algorithm for global search and feature selection

引用

SCIENTIFIC REPORTS 2025年第1期15卷 1-43页

作者： Liu, Jiacong Bi, Chunguang Chen, Huiling Heidari, Ali Asghar Chen, He Jilin Agr Univ Coll Informat Technol Changchun 130118 Peoples R China Wenzhou Univ Dept Comp Sci & Artificial Intelligence Wenzhou 325035 Peoples R China Univ Tehran Coll Engn Sch Surveying & Geospatial Engn Tehran Iran

The sine cosine algorithm (SCA) is a popular population-based optimization technique that utilizes sine and cosine functions to navigate complex search spaces. However, its inherent simplicity can hinder optimal exploration-exploitation balance, particularly in high-dimensional problems, leading to slow convergence and reduced precision. To address these issues, we propose a novel triangular optimization (TO) strategy combined with a theft mechanism (TM), resulting in an enhanced algorithm named TTOSCA. We rigorously evaluate TTOSCA against 27 competing algorithms using the IEEE CEC2017 benchmark functions and apply the Wilcoxon signed-rank test to assess performance. Our results indicate that TTOSCA significantly improves precision and convergence speed. Furthermore, we develop a binary variant, BTTOSCA, to validate its effectiveness in discrete spaces through feature selection experiments on 17 datasets from UCI, including medical and high-dimensional gene data. Comparative analysis shows that BTTOSCA excels in both exploration and exploitation, achieving smaller feature subsets without compromising classification accuracy. This positions BTTOSCA as a powerful tool for feature selection in high-dimensional datasets.

关键词： sine cosine algorithm Swarm intelligence Feature selection Global optimization

来源：评论

学校读者我要写书评

暂无评论

Improved sine cosine algorithm for Optimization Problems Based on Self-Adaptive Weight and Social Strategy

引用

IEEE ACCESS 2023年 11卷 73053-73061页

作者： Chun, Ye Hua, Xu Jiangsu Vocat Coll Informat Technol Internet Things Engn Coll Wuxi 214001 Peoples R China Jiangnan Univ Sch Artificial Intelligence & Comp Sci Wuxi 214001 Peoples R China

The sine cosine algorithm (SCA) is a well-known optimization technique that utilizes sine and cosine functions to identify optimal solutions. Despite its popularity, the SCA has limitations in terms of low diversity, stagnation in local optima, and difficulty in achieving global optimization, particularly in complex large-scale problems. In response, we propose a novel approach named the Improved Weight and Strategy sine cosine algorithm (IWSCA). The IWSCA achieves this by introducing novel self-adaptive weight and social strategies that enable the algorithm to efficiently search for optimal solutions in complex large-scale problems. The performance of the IWSCA is evaluated with 23 benchmark test functions and the IEEE CEC 2019 benchmark suite, compare it to a state-of-the-art heuristic algorithm and two improved versions of the SCA. Our experimental results demonstrate that the IWSCA outperforms existing methods in terms of convergence precision and robustness.

关键词： sine cosine algorithm self-adaptive weight social strategy complex large-scale problems

来源：评论

学校读者我要写书评

暂无评论

Combined Emission Economic Load Dispatch with Renewable Energy Sources Employing Hybrid Statistical Multiswarm Particle Swarm Optimizer-sine cosine algorithm

引用

ELECTRIC POWER COMPONENTS AND SYSTEMS 2023年第9期51卷 871页

作者： Keswani, Rinki Verma, Harish Kumar Sharma, Shailendra Kumar Shri GS Inst Technol & Sci Indore India

Due to the increase in environmental concerns, it becomes mandatory now to focus on energy management and the planning of resources. An integration of distributed generation resources with conventional sources is gaining popularity. The hybrid modeling of the power system poses a complex and challenging optimization problem without getting trapped in a local optimum. A novel Hybrid Statistical Multiswarm Particle Swarm Optimizer-sine cosine algorithm (HSMPSO-SCA) is developed in this paper, and its performance is evaluated on various test benchmark functions. The real operating conditions such as valve point loading, prohibited zones, ramp rate limits and uncertainties in solar and wind power generation for the IEEE 30 bus system are considered for combined emission economic load dispatch (CEELD). The performance of the HSMPSO-SCA is also analyzed for the solution of CEELD for various standard test systems with interaction of solar and wind plants. The efficacy of the proposed HSMPSO-SCA is found to be much better than various metaheuristics, hybrid and multi-agent algorithms in minimizing cost along with emissions optimally and achieves better accuracy and a faster convergence rate.

关键词： combined emission economic load dispatch statistical multi swarm particle swarm optimization sine cosine algorithm solar energy wind energy uncertainty

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：