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Article
An orthogonal electric fish optimization algorithm with quantization for global numerical optimization
In the past few decades, meta-heuristic algorithms have become a research hotspot in the field of evolutionary computing. The electric fish optimization algorithm (EFO) is a new meta-heuristic algorithm. Becau...
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Article
Adaptive chimp optimization algorithm with chaotic map for global numerical optimization problems
Chimp optimization algorithm (ChOA) is a meta-heuristic algorithm inspired by individual intelligence and sexual motivation during group hunting. It is designed to speed up the convergence of the optimal solut...
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Article
Defect of Archimedes optimization algorithm and its verification
Archimedes optimization algorithm (AOA) is a new meta-heuristic algorithm which is based on Archimedes principle and mimics the buoyancy force received by an object in water. The AOA is designed according to p...
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Article
Polyaniline functionalized CoAl-layered double hydroxide nanosheets as a platform for the electrochemical detection of carbaryl and isoprocarb
The preparation of the polyaniline/CoAl-layered double hydroxide composite (PANI/CoAl-LDH) is presented by ultrasonic mixing the uniform PANI- and CoAl-LDH-building blocks, both of which are synthesized in a m...
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Article
Amperometric sensing of catechol by using a nanocomposite prepared from Ag/Ag2O nanoparticles and N,S-doped carbon quantum dots
This work describes the synthesis of a nanocomposite consisting of Ag2O, silver nanoparticles and N,S-doped carbon quantum dots (Ag2O/Ag@NS-CQD). The NS-CQD were prepared by hydrothermal treatment of p-aminobenze...
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Article
A modified particle swarm optimization for large-scale numerical optimizations and engineering design problems
Particle swarm optimization (PSO) has attracted the attention of many researchers because of its simple concept and easy implementation. However, it suffers from premature convergence due to quick loss of popu...
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Article
Integrating opposition-based learning into the evolution equation of bare-bones particle swarm optimization
Bare-bones particle swarm optimization (BPSO) is attractive since it is parameter free and easy to implement. However, it suffers from premature convergence because of quickly losing diversity, and the dimensi...