Results 51 to 60 of about 240,959 (297)

Genetic algorithm and neural network hybrid approach for job-shop scheduling [PDF]

, 1998
Copyright @ 1998 ACTA PressThis paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems.
Wang, D, Yang, S, Zhao, K
core  

Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

, 2004
The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels.
Galantucci, L. M., Percoco, G., Spina, R.   +2 more
core   +2 more sources

Genetic Algorithm for quick finding of diatomic molecule potential parameters

, 2020
Application of Genetic Algorithm (GA) for determination of parameters of an analytical representation of diatomic molecule potential is presented. GA can be used for finding potential characteristics of an electronic energy state which can be described ...
Koperski, Jaroslaw, Urbanczyk, Tomasz
core   +1 more source

Towards a framework for designing full model selection and optimization systems [PDF]

, 2013
People from a variety of industrial domains are beginning to realise that appropriate use of machine learning techniques for their data mining projects could bring great benefits.
Mayo, Michael, Pfahringer, Bernhard, Sun, Quan   +2 more
core   +1 more source

Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases With Application to Scleroderma

Arthritis Care &Research, EarlyView.
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim, John Scott, Lauren Fisher, Lauren N. Smith, Willie Stewart, Adrianne Woods, Rob Smithwright, Diane Koher, Parastoo Aslanbeik, Aalok B. Shah, Brad Tibbils, Samantha I. Pitts, Ayse P. Gurses, Yushi Yang, Ana‐Maria Orbai, Antony Rosen, Laura K. Hummers, Scott L. Zeger, Ami A. Shah   +18 more
wiley   +1 more source

Soft-Information Assisted Near-Optimum Nonlinear Detection for BLAST-type Space Division Multiplexing OFDM Systems

, 2007
In this contribution, a nonlinear hybrid detection scheme based on a novel soft-information assisted Genetic Algorithm (GA) is proposed for a Turbo Convolutional (TC) coded Space Division Multiplexing (SDM) aided Orthogonal Frequency Division ...
Akhtman, Jos, Hanzo, Lajos, Jiang, Ming
core   +1 more source

Crossing Over Genetic Algorithms: The Sugal Generalised GA

Journal of Heuristics, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Exploring Patients’ Profiles Associated With the Resolution of Acute Calcium Pyrophosphate Arthritis Treated With Colchicine and Prednisone: Post Hoc Analysis of a Randomized Controlled Trial

Arthritis Care &Research, EarlyView.
Objective The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyrophosphate (CPP) crystal arthritis. Methods We conducted a post hoc analysis of the COLCHICORT trial, which compared colchicine and prednisone for the treatment of acute CPP crystal arthritis, using a ...
Tristan Pascart, Laurène Norberciak, Pascal Richette, Pierre Robinet, Aurore Pacaud, Gauthier Marchasson, Thibault Rabin, Hélène Luraschi, Pierre Maciejasz, Anne‐France Georgel, Augustin Latourte, Hang‐Korng Ea, Sébastien Ottaviani, Charlotte Jauffret, Vincent Ducoulombier   +14 more
wiley   +1 more source

Cooperative co-evolution of GA-based classifiers based on input increments [PDF]

, 2007
Genetic algorithms (GAs) have been widely used as soft computing techniques in various applications, while cooperative co-evolution algorithms were proposed in the literature to improve the performance of basic GAs.
Guan, SU, Zhu, F
core   +2 more sources

GA: A Package for Genetic Algorithms inR

Journal of Statistical Software, 2013
Genetic algorithms (GAs) are stochastic search algorithms inspired by the basic principles of biological evolution and natural selection. GAs simulate the evolution of living organisms, where the fittest individuals dominate over the weaker ones, by mimicking the biological mechanisms of evolution, such as selection, crossover and mutation.
openaire   +6 more sources