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The paper describes and discusses the application of a guided evolutionary approach for the optimization of water distribution networks. Initially developed for the Battle of the Water Networks II (BWN-II), the approach was adapted and improved for competi ...
In this paper we describe a new methodology for optimising building and urban geometric forms for the utilisation of solar irradiation, whether by passive or active means. For this we use a new evolutionary algorithm(a hybrid CMA-ES/HDE algorithm) to searc ...
This paper investigates the performance of 6 versions of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with restarts on a set of 28 noiseless optimization problems (including 23 multi-modal ones) designed for the special session on real-paramete ...
The purpose of this paper is to analyse the optimal three-dimensional form of buildings that minimise energy consumption due to solar irradiation. We use an evolutionary algorithm (hybrid CMA-ES/HDE algorithm) already applied to maximise solar energy utili ...
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and control. A method is presented for translating CPPNs into complete robots includin ...
This paper investigates the performance of 6 versions of Covariance Matrix Adaptation Evolution Strategy (CMAES) with restarts on a set of 28 noiseless optimization problems (including 23 multi-modal ones) designed for the special session on real-parameter ...
Evolutionary algorithms are heuristic methods that operate on a population of individuals, which represent candidate solutions to optimization problems. Individuals with better quality, or fitness, are reproduced at a higher rate than less fit individuals ...
A novel hybrid evolutionary neural network method to generate multiple spectrum-compatible artificial earthquake accelerograms (SCAEAs) is presented. Genetic algorithm is employed to optimize the weight values of networks. In order to improve the training ...
This study proposes a new technique for real-time building energy modelling and event detection using kernel regression. We show that this technique can exceed the performance of conventional neural network algorithms, and do so by a large margin when the ...
The manual design of con- trol systems for robotic devices can be challenging. Methods for the automatic synthesis of control systems, such as the evolution of artificial neural networks, are thus widely used in the robotics community. However, in many rob ...
Institute of Electrical and Electronics Engineers2010
