Nature-Inspired Computing: Swarm-Intelligence Based AlgorithmsNazmul H. SiddiqueHojjat Adeli
Don't hesitate to contact me Evolutionary Algorithms– Genetic Algorithm Background • Inspired byNeo-Darwinsim –Darwin’s hypothesis of Natural Selection –survival of the fittest(most adaptable) –Discovery of the genetic code in DNA • Evolutionary Algorithms –Started in the 1960’s ...
Gravitational Search Algorithm (GSA) is a population-based search algorithm inspired by the law of gravity and mass interaction [42]. The algorithm considers agents as objects consisting of different masses. The entire agents move due to the gravitational attraction force acting between them, and th...
Sandia National Laboratories (2021). A discussion on the need for innovative co-design tools and architectures to integrate neuromorphic computing, inspired by properties of the brain, with conventional computing platforms to enhance high-performance-computing capabilities. ...
Neuromorphic computing draws inspiration from the brain to provide computing technology and architecture with the potential to drive the next wave of computer engineering1–13. Such brain-inspired computing also provides a promising platform for the deve
Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others ...
Nature inspired algorithm plays a very vibrant role in solving the different optimization problems these days. The fundamental attitude of naturalistic approaches is to boost the competence, improvement, proficiency, success in the task except from it to help in underrating the energy use, cost, siz...
在人工智能如火如荼的今天,基于人脑的“脉冲”(spiking)模拟计算框架下的脉冲神经网络(SNN)、神经形态计算(neuromorphic computing)有望在实现人工智能的同时,降低计算平台的能耗。这一跨学科领域以硅电路实现生物中的神经环路(circuit)为起点,现已发展到包括基于脉冲的编码以及事件驱动表示的算法的硬件实现。
在人工智能如火如荼的今天,基于人脑的“脉冲”(spiking)模拟计算框架下的脉冲神经网络 (SNN)、神经形态计算(neuromorphic computing)有望在实现人工智能的同时,降低计算平台的能耗。这一跨学科领域以硅电路实现生物中的神经环路(circuit)为起点,现已发展到包括基于脉冲的编码以及事件驱动表示的算法的硬件实现。
The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applicati...