Titlebook: Applying Particle Swarm Optimization; New Solutions and Ca Burcu Ad?güzel Mercang?z Book 2021 The Editor(s) (if applicable) and The Author(

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Constriction Coefficient-Based Particle Swarm Optimization and Gravitational Search Algorithm for Im on pixel intensities. In this work, a new image segmentation method has been introduced based on the constriction coefficient-based particle swarm optimization and gravitational search algorithm (CPSOGSA). The random samples of the image histogram act as searcher agents of the CPSOGSA. Besides, the

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An Overview of the Performance of PSO Algorithm in Renewable Energy Systemss and problems. Among the most important challenges is finding the smart technologies and algorithms which are capable of achieving efficient solutions. This chapter provides an expanded view of the uses of the particle swarm optimization (PSO) algorithm in the renewable energy systems field. Additi

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Application of PSO in Distribution Power Systems: Operation and Planning Optimizationcreasingly highly complex system. The liberalization of the energy market and the introduction of distributed generation and, in particular, distributed renewable energy resources (DRES) have raised both opportunities and challenges that need to be tackled. Thus, complex issues related to the operat

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Utility: Theories and Modelsrg paradoxes criticize expected utility theory. Tversky and Kahneman (Econometrica, 47: 263–291, 1979) present that the expected utility axioms are violated for more reasonable lottery alternatives than in the Allais paradox and put a link between finance and psychology. The prospect theory of Tvers

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Behavioral Portfolio Theoryl explanation of the idea of diversifying investments and is the cornerstone of many risk models developed such as capital asset pricing model and arbitrage pricing model in later years. The empirical studies reveal that investors do not act rationally as financial models assume and anomalies occur.

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A Comparative Study on PSO with Other Metaheuristic MethodsO), artificial bee colony (ABC) algorithm, particle swarm optimization (PSO), tabu search (TS), harmony search (HS), firefly algorithm (FF), cuckoo search (CS), bat-inspired algorithm (BA), water wave optimization (WWO), clonal selection algorithm (CLONALG), chemical reaction optimization (CRO), sin

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The PSO Family: Application to the Portfolio Optimization Problemoney of having sold it. This mathematical situation is known as a Pareto front, which aims to show the boundary of the nonlinear equivalence region of the corresponding decision problem. In this chapter, we introduce the concept of uncertainty in high-dimensional problems, proposing the particle swa