A Meta-Heuristic Algorithm Based on the Happiness Model


Makale | 2023 | Studies in Computational Intelligence , pp.109 - 126

Recent work has attempted to determine the appropriate global minimum for complex problems. The paper presents a population and direct-based swarm optimization algorithm called the happiness optimizer (HPO) algorithm. An HPO algorithm is designed based on personal behavior and demonstrated in 30 and 100 dimensions on benchmark functions. The model includes four questions: “what do you want?”, “what do you have?”, “what do others have?”, and “what happened?”, which guide the development of a happiness behavior model. By considering the balancing between exploration and exploitation operators in the search space problem, efficiency, r . . .obustness, and stability were demonstrated for synthetic and real cases. For comparison, our proposed algorithm and some well-known algorithms will be 30 times applied on the benchmark functions and then compared with statistical value and Wilcoxon signed-rank test. As a consequence, the performance, reliability, and stability of our work have been demonstrated better than the others. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG Daha fazlası Daha az

Multi-circle Detection Using Multimodal Optimization


Makale | 2023 | Book Series

Object and shape detection in digital image were one of the hot topic over the last two decades. Especially automatic multi circle detection has received more attention over last years. Hough transform (HT) is a well-known and most popular method for lines and circles detection. However, HT has huge computational complexity expense. This paper proposed a new successful heuristic method to reduce computation time and improve the speed of HT for circle detection. In this proposed method the edges information of the image is obtained by means of Robert edge detection. Then, multimodal particle swarm optimization (PSO) and local search . . .is employed to locate all exciting circle in the image. The experiments on benchmark images show that our scheme can perform multi circle detection successfully. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG Daha fazlası Daha az

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