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International Journal of Swarm Intelligence Research最新文献

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Research on Electric Load Forecasting and User Benefit Maximization Under Demand-Side Response 需求侧响应下的电力负荷预测与用户利益最大化研究
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2023-02-03 DOI: 10.4018/ijsir.317112
Wenna Zhao, Guoxing Mu, Yanfang Zhu, Limei Xu, Deliang Zhang, Hongwei Huang
{"title":"Research on Electric Load Forecasting and User Benefit Maximization Under Demand-Side Response","authors":"Wenna Zhao, Guoxing Mu, Yanfang Zhu, Limei Xu, Deliang Zhang, Hongwei Huang","doi":"10.4018/ijsir.317112","DOIUrl":"https://doi.org/10.4018/ijsir.317112","url":null,"abstract":"In this paper, the real-time changes of demand-side response factors are accurately considered. First, CNN is combined with BiLSTM network to extract the spatio-temporal features of load data; then an attention mechanism is introduced to automatically assign the corresponding weights to the hidden layer states of BiLSTM. In the optimization part of the network parameters, the PSO algorithm is combined to obtain better model parameters. Then, considering the average reduction rate of various users under energy efficiency resources and the average load rate under load resources on the original forecast load and the original forecast load, the original load is superimposed with the response load considering demand-side resources to achieve accurate load forecast. Finally, “price-based” time-of-use tariff and “incentive-based” emergency demand response are selected to build a load response model based on the principle of maximizing customer benefits. The results show that demand-side response can reduce the frequency and magnitude of price fluctuations in the wholesale market.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49423852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sine-Cosine Algorithm for the Dynamic Economic Dispatch Problem With the Valve-Point Loading Effect 考虑阀点负荷影响的动态经济调度问题的正弦余弦算法
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2023-01-20 DOI: 10.4018/ijsir.316801
Jatin M. Soni, K. Bhattacharjee
{"title":"Sine-Cosine Algorithm for the Dynamic Economic Dispatch Problem With the Valve-Point Loading Effect","authors":"Jatin M. Soni, K. Bhattacharjee","doi":"10.4018/ijsir.316801","DOIUrl":"https://doi.org/10.4018/ijsir.316801","url":null,"abstract":"Dynamic economic dispatch (DED) deals with the allocation of predicted load demand over a certain period of time among the thermal generating units at minimum fuel cost. The objective function of DED becomes highly complex and nonlinear after considering various operating constraints like valve point loading, ramp rate limit, transmission loss, and generation limits. In this study, the sine-cosine algorithm has been presented to solve the DED problem with various constraints. The randomly placed swarm finds an optimum solution according to their fitness values and keeps the path towards the best solution attained by each swarm. The swarm avoid local optima in the exploration stage and move towards the solution exploitation stage using sine and cosine functions. The proposed technique has been tested in several test systems. The results obtained by the proposed technique have been compared with those obtained by other published methods employing the same test systems. The results validate the superiority and the effectiveness of the proposed technique over other well-known techniques.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46559037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Retrospection and investigation of ANN-based MPPT technique in comparison with soft computing-based MPPT techniques for PV solar and wind energy generation system 对基于人工神经网络的光伏、太阳能和风能发电系统中基于软计算的MPPT技术进行了回顾和研究
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2023-01-01 DOI: 10.1504/ijsi.2023.10055513
Sunita Chahar, D. K. Yadav
{"title":"Retrospection and investigation of ANN-based MPPT technique in comparison with soft computing-based MPPT techniques for PV solar and wind energy generation system","authors":"Sunita Chahar, D. K. Yadav","doi":"10.1504/ijsi.2023.10055513","DOIUrl":"https://doi.org/10.1504/ijsi.2023.10055513","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"216 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75594162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Local Optimal-Oriented Pattern and Exponential Weighed-Jaya Optimization-Based Deep Convolutional Networks for Video Summarization 面向局部最优模式和指数加权jaya优化的深度卷积网络视频摘要
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-07-01 DOI: 10.4018/ijsir.304403
L. Jimson., John Patrick Ananth
{"title":"Local Optimal-Oriented Pattern and Exponential Weighed-Jaya Optimization-Based Deep Convolutional Networks for Video Summarization","authors":"L. Jimson., John Patrick Ananth","doi":"10.4018/ijsir.304403","DOIUrl":"https://doi.org/10.4018/ijsir.304403","url":null,"abstract":"Video summarization is used to generate a short summary video for providing the users a very useful visual and synthetic abstract of the video content. There are various methods are developed for video summarization in existing, still an effective method is required due to some drawbacks, like cost and time. The ultimate goal of the research is to concentrate on an effective video summarization methodology that represents the development of short summary from the entire video stream in an effective manner. At first, the input cricket video consisting of number of frames is given to the keyframe generation phase, which is performed based on Discrete Cosine Transform (DCT) and Euclidean distance for obtaining the keyframes. Then, the residual keyframe generation is carried out based on Deep Convolutional Neural Network (DCNN), which is trained optimally using the proposed Exponential weighed moving average-Jaya (EWMA-Jaya) optimization.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"13 1","pages":"1-21"},"PeriodicalIF":1.1,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70470796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A review of 0-1 knapsack problem by nature-inspired optimisation algorithms 基于自然启发优化算法的0-1背包问题综述
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.1504/ijsi.2022.10051132
Harish Sharma, Nirmala Sharma, R. Chauhan
{"title":"A review of 0-1 knapsack problem by nature-inspired optimisation algorithms","authors":"Harish Sharma, Nirmala Sharma, R. Chauhan","doi":"10.1504/ijsi.2022.10051132","DOIUrl":"https://doi.org/10.1504/ijsi.2022.10051132","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"48 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74701223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Logistic Map and Exponential Scaling Factor based Differential Evolution 基于Logistic映射和指数尺度因子的差分进化
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.2022010119
{"title":"Logistic Map and Exponential Scaling Factor based Differential Evolution","authors":"","doi":"10.4018/ijsir.2022010119","DOIUrl":"https://doi.org/10.4018/ijsir.2022010119","url":null,"abstract":"Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44387696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The web ad-click fraud detection approach for supporting to the online advertising system 一种支持网络广告系统的网络广告点击欺诈检测方法
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.1504/IJSI.2022.10039450
P. Keserwani, M. C. Govil, E. Pilli
{"title":"The web ad-click fraud detection approach for supporting to the online advertising system","authors":"P. Keserwani, M. C. Govil, E. Pilli","doi":"10.1504/IJSI.2022.10039450","DOIUrl":"https://doi.org/10.1504/IJSI.2022.10039450","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"14 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84334890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method 基于优化的蚁群启发式结核病图像分割
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.2022010113
{"title":"Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method","authors":"","doi":"10.4018/ijsir.2022010113","DOIUrl":"https://doi.org/10.4018/ijsir.2022010113","url":null,"abstract":"Tuberculosis (TB) is a worldwide health crisis and is the second primary infectious disease that causes death next to human immunodeficiency virus. In this work, an attempt has been made to detect the presence of bacilli in sputum smears. The smear images recorded under standard image acquisition protocol are subjected to hybrid Ant Colony Optimization (ACO)-morphological based segmentation procedure. This method is able to retain the shape of bacilli in TB images. The segmented images are validated with ground truth using overlap, distance and probability-based measures. Significant shape-based features such as area, perimeter, compactness, shape factor and tortuosity are extracted from the segmented images. It is observed that this method preserves more edges, detects the presence of bacilli and facilitates direct segmentation with reduced number of redundant searches to generate edges. Thus this hybrid segmentation technique aid in the diagnostic relevance of TB images in identifying the objects present in them.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45098837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
COMPARATIVE ANALYSIS OF BIO-INSPIRED OPTIMIZATION ALGORITHMS IN NEURAL NETWORK BASED DATA MINING CLASSIFICATION 基于神经网络的数据挖掘分类中仿生优化算法的比较分析
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.2022010114
{"title":"COMPARATIVE ANALYSIS OF BIO-INSPIRED OPTIMIZATION ALGORITHMS IN NEURAL NETWORK BASED DATA MINING CLASSIFICATION","authors":"","doi":"10.4018/ijsir.2022010114","DOIUrl":"https://doi.org/10.4018/ijsir.2022010114","url":null,"abstract":"It always helps to determine optimal solutions for stochastic problems thereby maintaining good balance between its key elements. Nature inspired algorithms are meta-heuristics that mimic the natural activities for solving optimization issues in the era of computation. In the past decades, several research works have been presented for optimization especially in the field of data mining. This paper addresses the implementation of bio-inspired optimization techniques for machine learning based data mining classification by four different optimization algorithms. The stochastic problems are overcome by training the neural network model with techniques such as barnacles mating , black widow optimization, cuckoo algorithm and elephant herd optimization. The experiments are performed on five different datasets, and the outcomes are compared with existing methods with respect to runtime, mean square error and classification rate. From the experimental analysis, the proposed bio-inspired optimization algorithms are found to be effective for classification with neural network training.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41649823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
On the Design and Optimization of Test Cases Using an Improved Artificial Bee Colony Algorithm-Based Swarm Intelligence Approach 基于改进人工蜂群算法的群体智能测试用例设计与优化
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.309941
Jeya Mala Dharmalingam, R. Prabha
{"title":"On the Design and Optimization of Test Cases Using an Improved Artificial Bee Colony Algorithm-Based Swarm Intelligence Approach","authors":"Jeya Mala Dharmalingam, R. Prabha","doi":"10.4018/ijsir.309941","DOIUrl":"https://doi.org/10.4018/ijsir.309941","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"742 1","pages":"1-20"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70471482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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