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检索条件"主题词=Whale optimization algorithms"

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A Novel whale optimization Algorithm with Sparrow algorithm and Golden Sine Leading Strategy

A Novel Whale Optimization Algorithm with Sparrow algorithm ...

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Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Shixian Huang Huajuan Huang College of electronic information Guangxi University for Nationalities Nanning China

ISBN: (纸本)9781665426312

whale optimization algorithm (WOA) is a recently proposed optimization algorithm. In view of the slow convergence velocity, low precision and hard to get away from local optimum of WOA algorithm, this paper puts forward a whale optimization algorithm with sparrow algorithm and golden sine leading strategy (SGSWOA). First, the location update rule of the producer in the sparrow algorithm is integrated into the Encircling prey stage of WOA to increase the search space of the algorithm and escape from the local optimum. Then combined with the golden sine leading strategy, it can balance exploration and development capabilities and enhance the performance of WOA algorithm. Finally, by optimizing 16 benchmark functions and applying the SGSWOA algorithm to practical engineering optimization problems, the experimental results display the SGSWOA algorithm has better convergence accuracy, convergence speed, and robustness.

关键词： Benchmark testing whale optimization algorithms Robustness Artificial intelligence optimization Convergence

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Smart Grid based decentralized Peer-to-Peer Energy Trading Using whale optimization Algorithm

Smart Grid based decentralized Peer-to-Peer Energy Trading U...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Nazila Razzaghi-Asl Jafar Tanha Mehdi Nabatian Negin Samadi University of Tabriz Tabriz Iran Azarbaijan Shahid Madani University Tabriz Iran

ISBN: (纸本)9781665409391

Increased penetration of distributed energy resources (DERs) in smart grids (SG) has sparked a new movement to consumer-centric structure as marketplaces based on peer-to-peer (P2P) models. Participants can directly agree bilateral power transactions in P2P markets to balance producers and consumers. The trading mechanism should be well-designed to encourage participants to operate actively in the trading activity. This article proposes a trading strategy for P2P strategy in SG. The proposed framework is modeled using the whale optimization algorithm (WOA). In order to evaluate the proposed optimization method, particle swarm optimization (PSO) and classical optimization methods are carried out. The compared results show that the convergency of proposed method is faster than PSO algorithm.

关键词： Signal processing algorithms optimization methods Signal processing whale optimization algorithms Peer-to-peer computing Smart grids Distributed power generation

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Optimal Configuration and Economic Evaluation of Hybrid Energy Storage Using an Improved whale optimization Algorithm

Optimal Configuration and Economic Evaluation of Hybrid Ener...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yu Chen Liping Guo Chun Yang Jinyu Zhai College of Electric Power Inner Mongolia University of Technology Hohhot Inner Mongolia China Engineering Research Center of Large Energy Storage Technology Ministry of Education Hohhot Inner Mongolia China

ISBN: (数字)9798331516611

ISBN: (纸本)9798331516628

The new distribution network faces the problems of medium and long-period storage difficulties, low carbon and economy to be improved. Optimizing the configuration of hybrid energy storage will help to promote the goal of “double carbon.” The optimal configuration and economic evaluation of the hybrid energy storage composed of lithium battery energy storage and hydrogen energy storage are carried out in order to give full play to the role of energy storage in the new distribution network in this paper. Based on the sensitivity of network losses and the structural characteristics of the distribution network, optimal connection points for the hybrid storage system are identified. A bi-level optimization model is established, incorporating both capital investment and operational costs. The lower-level optimization focuses on minimizing operational costs to determine the optimal energy storage capacity, while the upper-level optimization aims to minimize the overall annual cost of the system. The Topsis method is used to select the Pareto-optimal solutions, yielding the optimal configuration of the hybrid energy storage system's capacity. During the optimization process, the fitness evaluation criterion from the simulated annealing algorithm is integrated into the whale optimization algorithm, which enhances the algorithm's ability to avoid premature convergence and accelerates its convergence speed. An economic evaluation framework for the distribution network is developed, and four different energy storage planning scenarios are assessed using a combination of gray relational analysis and the entropy weighting method. Simulation results based on an improved IEEE 33-node distribution network show that the optimized hybrid energy storage system can reduce line losses, improve voltage quality at nodes, enhance the utilization of distribution transformers, and significantly increase CO 2 and SO 2 emission reductions. Both operational and environmental performance indicat

关键词： Costs Sensitivity Distribution networks Simulated annealing whale optimization algorithms Planning Carbon optimization Energy storage Convergence

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Reconfiguration of the Distribution Network using a whale optimization Algorithm

Reconfiguration of the Distribution Network using a Whale Op...

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IEEE Students' Conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Akash Solanki Shweta Mehroliya Anoop Arya Shilpi Tomar Karuna Nikum Department of Electrical Engineering Maulana Azad National Institute of technology Bhopal India Department of Electrical Engineering Samrat Ashok Technological Institute Vidisha India Department of Electrical Engineering Thakur College of Engineering and Technology Mumbai India

The most prevalent and crucial approach to energy system reconfiguration can be used to enhance the power system for distribution, which is covered in this paper. Reconfiguration entails modifying the status of switches in the network's radial distribution topology. The aim is to enhance the power profile while lowering the complete loss of power. This problem was solved using a variety of optimization strategies, including heuristic methods, which are more effective in this case, and classical optimization, which is a time-consuming methodology. To find the best case in the reconfiguration problem, the whale optimization algorithm (WOA), a modern heuristic optimization approach, is used. When solving discrete optimization issues, the WOA is quite effective. The outcomes of WOA are contrasted with those of several heuristic methods (33 bus systems and 69 bus systems).

关键词： Network topology Heuristic algorithms Power distribution Voltage Distribution networks whale optimization algorithms Power system reliability

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Pollution Flashover Pre-warning Method Based on Beluga whale optimization Algorithm

Pollution Flashover Pre-warning Method Based on Beluga Whale...

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Power and Electrical Technology Conference (APET), Asia

作者： Chaoying Fang Yunchu Cheng Jun Xu Xiaojie Wang Jiafeng Lin Wei Gong Electric Power Research Institute State Grid Fujian Electric Power Co. Ltd. Fuzhou China Fujian Zhongshisuo Electric Power Testing & Commissioning Co. Ltd. Fuzhou China

ISBN: (数字)9798350367690

ISBN: (纸本)9798350367706

The problem of pollution flashover of transmission lines seriously interferes with the safety and stability of the power grid system, and insulators occur pollution flashover has a close connection with meteorological conditions. In order to prevent pollution flashover disasters, a pollution flashover pre-warning model considering meteorological data is constructed, and a pre-warning method of the risk of pollution flashover based on the beluga optimization algorithm is proposed. Firstly, the meteorological characteristic quantities are screened according to the fouling mechanism; secondly, the risk assessment model of pollution flashover disaster of transmission lines is constructed based on the meteorological parameters; then, the parameters of the pollution flashover pre-warning model are optimized by the beluga optimization algorithm; finally, an example analysis of line pollution flashover is carried out to verify the effectiveness of the proposed method. The results of the study can provide technical references for power grid anti-pollution flashover work.

关键词： Pollution Rain Power transmission lines Surface contamination Flashover Insulators whale optimization algorithms Power grids Surface treatment optimization

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An Improvement on Exploration Step of whale optimization Algorithm with Levy Distribution for Classification Problems

An Improvement on Exploration Step of Whale Optimization Alg...

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Big Data Analytics and Practices (IBDAP), International Conference on

作者： Sakkayaphop Pravesjit Krittika Kantawong Natdanai Kamkhad Saksit Sabaiporn Jantawan Monchanuan Duangjai Jitkongchuen Arit Thammano Panchit Longpradit School of Information and Communication Technology University of Phayao Phayao Thailand Big Data Instutite Bangkok Thailand Facluty of Information Technology King Mongkut's Institute of Technology Ladkrabang Ladkrabang Thailand Faculty of Social Sciences and Humanities Mahidol University Nakhon Pathom Thailand

ISBN: (数字)9798350391749

ISBN: (纸本)9798350391756

The proposed system represents an enhanced movement in search of food of whale optimization Algorithm (WOA), based on Levy distribution for image classification of grape leaf disease. In the preprocessing, the proposed system uses convolution kernels to transform images into input data within the range of (0,1). Thereafter, the Levy distribution is incorporated into the WOA model as an exploration search mechanism. A grape leaf dataset from the Plant Village project (***), consisting of 4062 labeled images with dimensions of 256 by 256 pixels and divided into four classes -healthy, Black Rot, Black Measles, and Isariopsis leaf spot -is used to evaluate the performance of the proposed system. Experimental results show that the proposed system is better than Visual Geometry Group (VGG16), Gray Level Co-occurrence Matrix (GLCM) with SVM, Low contrast haze reduction-neighborhood component analysis with SVM, and whale optimization algorithm (WOA).

关键词： Support vector machines Convolution Pipelines Data preprocessing Measles Transforms whale optimization algorithms

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An Improved Beluga whale optimization Algorithm Based on Chaotic Opposition-Based Learning and Adaptive Weighting Factor

An Improved Beluga Whale Optimization Algorithm Based on Cha...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Bingbing Zhang Jingqing Jiang Jiazhi Song College of Mathematics Science Inner Mongolia Minzu University Inner Mongolia China College of Computer Science and Technology Inner Mongolia Minzu University Inner Mongolia China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Beluga whale optimization (BWO) algorithm faces challenges such as slower convergence, lower accuracy, and instability for dealing with unimodal functions. To tackle these problems, we propose an enhanced version of Beluga whale optimization Algorithm (ABWO). ABWO algorithm incorporates chaotic Opposition-Based Learning (OBL) and adaptive weighting factor. We fuse Logistic and Tent chaotic mappings with OBL to ensure an even distribution of individuals in the initial solution space during initialization. Consequently, the population diversity is increased and the quality of the initial solution is better. The adaptive weighting factor $F$ is introduced in the exploitation phase. It increases and then decreases with each iteration. This adjustment enhances the guiding effect of the global optimal position on individual position updates in the early stage of BWO. It also enables the algorithm to execute more effective global searches in the middle stage. Meanwhile, the algorithm converges more quickly in the late stage. Overall, the solution accuracy and convergence stability of the algorithm are improved. On nine unimodal test functions, ABWO has better optimization and convergence performance compared with six basic algorithms. It also outperforms three improved beluga whale optimization algorithms proposed by other scholars.

关键词： Accuracy Fuses Market research whale optimization algorithms optimization Faces Computational intelligence Convergence Logistics

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Enhancement of Network Security in MANET By Using Guided whale optimization Algorithm (GWOA) for Solving Multiobjective optimization

Enhancement of Network Security in MANET By Using Guided Wha...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： N. Siva Naga Malleswari Dingari Kalpana S. Marlin N. Bala Sundara Ganapathy M. Arun P. Satyanarayana Department of ECE V. R. Siddhartha Engineering College Vijayawada India Department of Computer Science and Engineering Vignana Bharathi Institute of Technology Hyderabad India Department of EEE Guru Nanak Institutions Technical Campus Hyderabad India Department of Information Technology Panimalar Engineering College Chennai Tamil Nadu India Department of ECE Panimalar Engineering College Chennai Tamil Nadu India

Recently, wired networks have become more popular than wireless ones. Mobile Ad hoc Network, also used in the military (MANET). As the name suggests, military applications are the primary users of military or conventional MANET, which is designed to protect networks from intruders. The MANET is deployed for rescue missions during times of emergency, such as natural catastrophes or law enforcement activities. Each mobile node in a MANET is outfitted with both a Wi-Fi transmitter and receiver. In this paper we present that the Guided whale optimization Algorithm for Solving Multiobjective optimization for wireless security in MANET, Within the MANET, the best secured routing route is chosen with the assistance of a whale optimization algorithm (WOA), which is used within this article. When calculating the appropriateness of a routing route, the WOA algorithm takes into account both the trust factor and the physical separation among the nodes. The suggested routing technique has three steps: detecting the faith and distance-based statistics for each node, identifying a k-disjoint route, and establishing the optimum path based on those metrics. The indicators such as overhead as well as packet delivery rate are used in the examination of the effectiveness of the trust-based GWOA. When compared to other authentication methods, ours is the most efficient in terms of computing complexity.

关键词： Wireless communication Transmitters Authentication Routing whale optimization algorithms Complexity theory Communication system security

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Optimal DG Allocation Based on Pay-back Period by a Proposed Modification for Coronavirus Herd Immunity optimization

Optimal DG Allocation Based on Pay-back Period by a Proposed...

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International Middle-East Power System Conference, MEPCON

作者： Tarek A. Boghdady Elsayed Tag Eldin Howaida M. Ragab Ahdab Elmorshedy Electric Power Engineering Dept. Cairo University Giza Egypt Faculty of Engineering and Technology Future University in Egypt New Cairo Egypt Electric Power Engineering Dept. Ahram Canadian University Giza Egypt

ISBN: (纸本)9781665463645

Distribued Generations (DG) have economic, financial, and environmental benefits. DG reduces power losses in the distribution system but has a negative impact on the protection devices. In this article, the IEEE 33 bus system will be used and tested by adding up to three DG units using MATLAB/SIMULINK software. the optimization techniques that will be used are Grey Wolf Optimizer, whale optimization Algorithm, Genetic Algorithm, and Coronavirus Herd Immunity or COVID-19 optimization techniques to select the optimal site and size of the DG units based on the lowest pay-back period considering the voltage limits and power losses. The paper proposes a modified mutation operator for COVID-19 based on Gaussian and Cauchy mutations to have better performance and lower variance. The proposed algorithm is compared with the other optimization techniques. The proposed algorithm achieved better results, which proved to have competitive performance with state-of-the-art evolutionary algorithms.

关键词： COVID-19 Costs Software algorithms Voltage Linear programming whale optimization algorithms Software

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Frequency Regulation of a Distributed Power System via Modified whale optimization Algorithm

Frequency Regulation of a Distributed Power System via Modif...

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Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Rajendra Ku. Khadanga Sasmita Padhy Preeti Ranjan Sahu Sidhartha Panda Centurion University of Technology and Management Jatani Bhubaneswar Odisha INDIA National Institute of Science & Technology Berhampur Odisha INDIA Veer Surendra Sai University of Technology Burla Odisha INDIA

ISBN: (纸本)9781665426923

This paper proposes the modified methodology for the whale optimization Algorithm (WOA) which improves the first procedure known as Modified WOA algorithm. The modification is established by introducing some correction factors as CF l , CF2 to the original WOA algorithm. In the subsequent stage, the real application of the proposed approach in this field is finished by structuring an AFPID controller for frequency regulation of a Distributed energy power generation system DEPS. The DEPS incorporates renewable sources like photovoltaic, wind and storage gadgets. It is seen that MWOA based AFPID controller is increasingly compelling for the frequency control.

关键词： Photovoltaic systems Technological innovation Renewable energy sources Regulators Philosophical considerations whale optimization algorithms Power systems

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