Results 41 to 50 of about 235,286 (321)

Use of the q-Gaussian mutation in evolutionary algorithms [PDF]

, 2010
Copyright @ Springer-Verlag 2010.This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms.
A Obuchowicz, AE Eiben, AK Qin, AMC Souza, C García-Martínez, C Tsallis, C Tsallis, CY Lee, F Herrera, H Dong, H Wang, H-G Beyer, JA Vrugt, M Iwamatsu, M Lozano, MA Moret, N Hansen, N Noman, QH Nguyen, R Tinós, R Tinós, Renato Tinós, S Das, S García, S Umarov, Shengxiang Yang, W Thistleton, X Yao, X Yao   +28 more
core   +3 more sources

Enhancing Robot Path Planning Through a Twin-Reinforced Chimp Optimization Algorithm and Evolutionary Programming Algorithm

IEEE Access
The importance of efficient path planning (PP) cannot be overstated in the domain of robots, as it involves the utilization of intelligent algorithms to determine the optimal trajectory for robot to navigate between two given points.
Yang Zhang, Hu Zhang
doaj   +1 more source

Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

Applied Computational Intelligence and Soft Computing, 2011
Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization.
Biaobiao Zhang, Yue Wu, Jiabin Lu, K.-L. Du   +3 more
doaj   +1 more source

Evolutionary programming made faster [PDF]

IEEE Transactions on Evolutionary Computation, 1999
Evolutionary programming (EP) has been applied with success to many numerical and combinatorial optimization problems in recent years. EP has rather slow convergence rates, however, on some function optimization problems. In the paper, a "fast EP" (FEP) is proposed which uses a Cauchy instead of Gaussian mutation as the primary search operator.
null Xin Yao, null Yong Liu, null Guangming Lin   +2 more
openaire   +1 more source

Studying Parallel Evolutionary Algorithms: The cellular Programming Case [PDF]

, 1998
Parallel evolutionary algorithms, studied to some extent over the past few years, have proven empirically worthwhile—though there seems to be lacking a better understanding of their workings. In this paper we concentrate on cellular (fine-grained) models,
A. Loraschi, A. Tettamanzi, D. Andre, E. CantÚ-Paz, G. Rudolph, M. Oussaidene, M. Sipper, M. Sipper, M. Sipper, R. Das, T. Starkweather, W. Hordijk   +11 more
core   +2 more sources

Application of the evolutionary approach to structural and parametric identification of dynamic objects [PDF]

ITM Web of Conferences
The paper examines the evolutionary approach to structural and parametric identification of dynamic systems in the form of differential equations. The approach is based on a genetic programming algorithm to determine a structure of the equation and ...
Karaseva Tatiana
doaj   +1 more source

EP BASED PSO METHOD FOR SOLVING PROFIT BASED MULTI AREA UNIT COMMITMENT PROBLEM [PDF]

Journal of Engineering Science and Technology, 2015
This paper presents a new approach to solve the profit based multi area unit commitment problem (PBMAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method.
K. VENKATESAN, G. SELVAKUMAR, C. C. A. RAJAN   +2 more
doaj  

Pareto optimal approach in Multi-Objective Chaotic Mutation Immune Evolutionary Programming (MOCMIEP) for optimal Distributed Generation Photovoltaic (DGPV) integration in power system

Ain Shams Engineering Journal, 2019
The latest advancement in the technology, including the integration of the renewable energy resources, has become a recent trend in the power system infrastructure. Although, this can bring many benefits, excessive integration without proper planning may
S.A. Syed Mustaffa, I. Musirin, M.K. Mohamad Zamani, M.M. Othman   +3 more
doaj   +1 more source

Evolution of a robotic soccer player [PDF]

, 2002
Robotic soccer is a complex domain where, rather than hand-coding computer programs to control the players, it is possible to create them through evolutionary methods.
Walker, Matthew
core  

Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning‐Based Approaches

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser, Alice Bizeul, Meera Chitlur, Hugo Donato, Jelena Roganovic, Julia E. Vogt, Thomas Kühne   +6 more
wiley   +1 more source