Titlebook: Brain Storm Optimization Algorithms; Concepts, Principles Shi Cheng,Yuhui Shi Book 2019 Springer Nature Switzerland AG 2019 Computational I

動(dòng)脈

https://doi.org/10.1007/978-3-030-15070-9Computational Intelligence; Evolutionary Computation; Swarm Intelligence; Brain Storm Optimization; Opti

semiskilled

978-3-030-15072-3Springer Nature Switzerland AG 2019

支架

織布機(jī)

放肆的我

Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networksnal brain storm optimization referred to as OBSO is proposed to effectively solve the FSL problem. The FSL problem is transformed into a 0–1 integer programming problem. The difference between the reported overcurrent and expected overcurrent states of the feeder terminal units (FTUs) is used as the

生意行為

Multi-objective Differential-Based Brain Storm Optimization for Environmental Economic Dispatch Probronmental pollution. A novel Multi-objective Differential Brain Storm Optimization (MDBSO) algorithm is proposed to solve EED problem in this chapter. Different from the classical BSO, the clustering operation is designed in the objective space instead of solution space to improve the computing effi

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absolve

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態(tài)學(xué)

Brain Storm Optimization Algorithms for Solving Equations Systemslgorithm, which simulates the human brainstorming process, a form of human collective creativity. Mainly, in this chapter, two algorithms are proposed: the first for ES preconditioning and second for solving ES. First, is proposed a BSO method aiming the bandwidth reduction of sparse matrices, a pro