Battery thermal management: An optimization study of parallelized conjugate numerical analysis using Cuckoo search and Artificial bee colony algorithm

2021 ◽  
Vol 166 ◽  
pp. 120798
Author(s):  
Asif Afzal ◽  
A.D. Mohammed Samee ◽  
R.D. Jilte ◽  
Md. Tariqul Islam ◽  
A. Muthu Manokar ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Thermal Management ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Cuckoo Search ◽  
Bee Colony ◽  
Battery Thermal Management ◽  
Optimization Study

scholarly journals A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Chunhua Ju ◽  
Chonghuan Xu
Keyword(s):  
Numerical Analysis ◽  
Collaborative Filtering ◽  
Real World ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Clustering Algorithm ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Collaborative Recommendation ◽  
Filtering Approach

Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users’ preferences. In this paper, we propose a novel collaborative filtering recommendation approach based onK-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused byK-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark datasetMovieLensand a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

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