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International Journal of Swarm Intelligence Research最新文献

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Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures 基于深度学习框架和雷达特征的运动目标检测策略
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.304400
M. Kumar, P. R. Kumar
{"title":"Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures","authors":"M. Kumar, P. R. Kumar","doi":"10.4018/ijsir.304400","DOIUrl":"https://doi.org/10.4018/ijsir.304400","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"13 1","pages":"1-21"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70470777","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 Solving Economic Load Dispatch Problem with Penetration of Renewables 求解可再生能源渗透经济负荷调度问题的正弦余弦算法
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.299847
{"title":"Sine Cosine Algorithm for Solving Economic Load Dispatch Problem with Penetration of Renewables","authors":"","doi":"10.4018/ijsir.299847","DOIUrl":"https://doi.org/10.4018/ijsir.299847","url":null,"abstract":"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.","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":"47100559","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
Taylor CFRO-Based Deep Learning Model for Service-Level Agreement-Aware VM Migration and Workload Prediction-Enabled Power Model in Cloud Computing 云计算中基于cro的服务水平协议感知虚拟机迁移深度学习模型和工作负载预测能力模型
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.4018/ijsir.304724
R. Pushpalatha, B. Ramesh
{"title":"Taylor CFRO-Based Deep Learning Model for Service-Level Agreement-Aware VM Migration and Workload Prediction-Enabled Power Model in Cloud Computing","authors":"R. Pushpalatha, B. Ramesh","doi":"10.4018/ijsir.304724","DOIUrl":"https://doi.org/10.4018/ijsir.304724","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"13 1","pages":"1-31"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70470891","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
Deep Bi-directional LSTM network with CNN features for human emotion recognition in audio-video signals 基于CNN特征的深度双向LSTM网络在音视频信号中的人类情感识别
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.1504/ijsi.2022.10044505
Lovejit Singh
{"title":"Deep Bi-directional LSTM network with CNN features for human emotion recognition in audio-video signals","authors":"Lovejit Singh","doi":"10.1504/ijsi.2022.10044505","DOIUrl":"https://doi.org/10.1504/ijsi.2022.10044505","url":null,"abstract":"","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":"83229654","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: 3
Predictions of soil movements using persistence, auto-regression, and neural network models: a case-study in Mandi, India 使用持久性、自回归和神经网络模型预测土壤运动:印度曼迪的案例研究
IF 1.1
International Journal of Swarm Intelligence Research Pub Date : 2022-01-01 DOI: 10.1504/ijsi.2022.10043800
V. Dutt, Priyanka ., A. Maurya, Mohit Kumar, Pratik Chaturvedi, Ravinder Singh, K. V. Uday, Praveen Kumar, A. Pathania
{"title":"Predictions of soil movements using persistence, auto-regression, and neural network models: a case-study in Mandi, India","authors":"V. Dutt, Priyanka ., A. Maurya, Mohit Kumar, Pratik Chaturvedi, Ravinder Singh, K. V. Uday, Praveen Kumar, A. Pathania","doi":"10.1504/ijsi.2022.10043800","DOIUrl":"https://doi.org/10.1504/ijsi.2022.10043800","url":null,"abstract":"","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"98 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73427713","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
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