Results 331 to 340 of about 7,762,731 (372)
Some of the next articles are maybe not open access.
Genetic-Algorithm-Based Optimization Approach for Energy Management
IEEE Transactions on Power Delivery, 2013This paper proposes a new strategy to meet the controllable heating, ventilation, and air conditioning (HVAC) load with a hybrid-renewable generation and energy storage system.
A. Arabali +4 more
semanticscholar +1 more source
Genetic algorithms and evolution
Journal of Theoretical Biology, 1990The genetic algorithm (GA) as developed by Holland (1975, Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press) is an optimization technique based on natural selection. We use a modified version of this technique to investigate which aspects of natural selection make it an efficient search procedure.
Alasdair I. Houston +4 more
openaire +3 more sources
Genetic algorithm solution of economic dispatch with valve point loading
, 1993A genetics-based algorithm is proposed to solve an economic dispatch problem for valve point discontinuities. The algorithm utilizes payoff information of candidate solutions to evaluate their optimality.
D. C. Walters, G. Sheblé
semanticscholar +1 more source
IEEE International Conference on Computer Vision, 2017
The deep convolutional neural network (CNN) is the state-of-the-art solution for large-scale visual recognition. Following some basic principles such as increasing network depth and constructing highway connections, researchers have manually designed a ...
Lingxi Xie, A. Yuille
semanticscholar +1 more source
The deep convolutional neural network (CNN) is the state-of-the-art solution for large-scale visual recognition. Following some basic principles such as increasing network depth and constructing highway connections, researchers have manually designed a ...
Lingxi Xie, A. Yuille
semanticscholar +1 more source
Genetic algorithms in chemometrics
Journal of Chemometrics, 2012This review covers the application of Genetic Algorithms (GAs) in Chemometrics. The first applications of GAs in chemistry date back to the 1970s, and in the last decades, they have been more and more frequently used to solve different kinds of problems, for example, when the objective functions do not possess properties such as continuity ...
A. Niazi, LEARDI, RICCARDO
openaire +3 more sources
2004
Publisher Summary This chapter reviews the basics of genetic algorithms (GAs), briefly describes the schema theorem and the building block hypothesis, and explains feature selection based on GAs, as one of the most important applications of GAs. GAs differ from classical optimization and search procedures: (1) direct manipulation of a coding, (2 ...
openaire +3 more sources
Publisher Summary This chapter reviews the basics of genetic algorithms (GAs), briefly describes the schema theorem and the building block hypothesis, and explains feature selection based on GAs, as one of the most important applications of GAs. GAs differ from classical optimization and search procedures: (1) direct manipulation of a coding, (2 ...
openaire +3 more sources
2015
The essence of machine learning is the search for the best solution to our problem: to find a classifier which classifies as correctly as possible not only the training examples, but also future examples. Chapter 1 explained the principle of one of the most popular AI-based search techniques, the so-called hill-climbing, and showed how it can be used ...
openaire +2 more sources
The essence of machine learning is the search for the best solution to our problem: to find a classifier which classifies as correctly as possible not only the training examples, but also future examples. Chapter 1 explained the principle of one of the most popular AI-based search techniques, the so-called hill-climbing, and showed how it can be used ...
openaire +2 more sources
Putting More Genetics into Genetic Algorithms
Evolutionary Computation, 1998The majority of current genetic algorithms (GAs), while inspired by natural evolutionary systems, are seldom viewed as biologically plausible models. This is not a criticism of GAs, but rather a reflection of choices made regarding the level of abstraction at which biological mechanisms are modeled, and a reflection of the more engineering-oriented ...
Burke, DS +4 more
openaire +3 more sources
, 2002