Battle Royale Optimizer with a New Movement Strategy

Sara Akan | Taymaz Akan

Gamed-based is a new stochastic metaheuristics optimization category that is inspired by traditional or digital game genres. Unlike SI-based algorithms, individuals do not work together with the goal of defeating other individuals and winning the game. Battle royale optimizer (BRO) is a Gamed-based metaheuristic optimization algorithm that has been recently proposed for the task of continuous problems. This paper proposes a modified BRO (M-BRO) in order to improve balance between exploration and exploitation. For this matter, an additional movement operator has been used in the movement strate ...Daha fazlası

Makale 2022 Springer Science and Business Media Deutschland GmbH 87 Görüntülenme

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Estimation single output with a hybrid of ANFIS and MOPSO_HS

Aref Yelghı

Adaptive Neuro-Fuzzy Inference System (ANFIS) has gained popularity in recent years due to its predictive capabilities. Proper adjustment of ANFIS parameters is an optimization problem but integrating it with traditional optimization techniques has led to challenges such as local minima and slow convergence, resulting in obstacles to its prediction. Additionally, some researchers focusing on incorporating single-objective optimization often face issues with reliability and stability in parameter adjustment. This study, focused on multi-objective optimization, presents an algorithm that integra ...Daha fazlası

Makale 2024 Sakarya Universit7 ( 1 ) , pp. 1 - 126 14 Görüntülenme

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Battle royale optimizer for training multi-layer perceptron

Taymaz Akan

Artificial neural network (ANN) is one of the most successful tools in machine learning. The success of ANN mostly depends on its architecture and learning procedure. Multi-layer perceptron (MLP) is a popular form of ANN. Moreover, backpropagation is a well-known gradient-based approach for training MLP. Gradient-based search approaches have a low convergence rate therefore, they may get stuck in local minima, which may lead to performance degradation. Training the MLP is accomplished based on minimizing the total network error, which can be considered as an optimization problem. Stochastic op ...Daha fazlası

Makale 2021 Evolving Systems13 ( 4 ) , pp. 5 - 575 111 Görüntülenme Süresiz Ambargo

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A Smart and Mechanized Agricultural Application: From Cultivation to Harvest

Metin Zontul

Food needs are increasing day by day, and traditional agricultural methods are not responding efficiently. Moreover, considering other important global challenges such as energy sufficiency and migration crises, the need for sustainable agriculture has become essential. For this, an integrated smart and mechanism-application-based model is proposed in this study. This model consists of three stages. In the first phase (cultivation), the proposed model tried to plant crops in the most optimized way by using an automized algorithmic approach (Sand Cat Swarm Optimization algorithm). In the second ...Daha fazlası

Makale 2022 Applied Sciences-Basel12 ( 12 ) 268 Görüntülenme