[PDF] Top 20 Optimization of distribution networks using evolutionary algorithms
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Optimization of distribution networks using evolutionary algorithms
... Sizing of dis- tributed generation (DG) ...tion of new generators, in radial distribution systems, could minimize the total power loss, reactive power flow, and voltage ...placement of DGs. In ... See full document
146
Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.
... Evolutionary algorithms(EAs) are one of the most interesting types of guided random search ...theory of evolution. An EA adapts during the search process, using the information ... See full document
17
Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms
... multi-objective optimization algorithm, which combines simulated annealing (SA) with cost function based on both, multi-attribute decision making (MADM) and TOPSIS [7] to provide the driver with optimal ...data ... See full document
7
Tuning Up Fuzzy inference systems by using optimization algorithms for the classification of solar flares
... space of solutions since it works with parameters represented in fixed point, having a more reduced universe as compared to the representation in floating ...parameters of the database), or type M or X ... See full document
11
TítuloPredicting vertical urban growth using genetic evolutionary algorithms in Tokyo’s minato ward
... use of computer models to simulate urban growth is CA ...introduction of computation and selforganization, the traditional top-down approaches for the simulation of urban growth have shifted toward ... See full document
16
TítuloTopological active model optimization by means of evolutionary methods for image segmentation
... variability of the objects and conditions in the images, it is recom- mended to use a global search method to be able to reach global correct solutions in all the possible ...bound algorithms [40], ... See full document
176
Migrants Selection and Replacement in Distributed Evolutionary Algorithms for Dynamic Optimization
... utilization of Distributed Genetic Algorithms (dGAs), one of the domains still to be investigated for ...migrations of individuals. In this ar- ticle, we analyze the effect of the ... See full document
8
Solving the two dimensional cutting problem using evolutionary algorithms with penalty functions
... The optimization plays a central role in operations research/management science and engineering design ...conventional optimization techniques. One example of them is the Cutting Problem (CP), in ... See full document
10
Acceleration of a bacterial metabolic simulation using neural networks with optimization techniques
... information of each ...behavior of each individual present in the system, which is an independent entity or ...simulation of the behavior of the bacteria more ...spatial distribution ... See full document
116
Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks
... means of an analytical or simulation-based ...wireless networks, an optimization method is normally used (denoted in the figure as the ...potential of this approach lies on the construction ... See full document
279
Design of in-building wireless networks deployments using evolutionary algorithms
... includes a quality constraint of the indoor deploy- ment. This objective function evaluates the area of the enterprise scenario with simultaneous cov- erage of the minimum number of bas[r] ... See full document
19
Optimization of coefficients of lists of polynomials by evolutionary algorithms
... means of symbolic deterministic algorithms (see ...question of determining a parametrization with the smallest (in absolute value) integer coefficients is ...means of evolutionary ... See full document
9
A survey on financial applications of metaheuristics
... rebalancing of a portfolio of credit assets in order to achieve a desired overall risk ...point of view, the risk manager should distribute the credit risk among a diversified set of ...the ... See full document
24
Distributed Estimation of Distribution Algorithms for continuous optimization: how does the exchanged information influence their behavior?
... In general terms, EDAs are similar to Genetic Algorithms (GAs), but their main characteristic is the use of probabilistic models to extract information from the most promising individu[r] ... See full document
24
Artificial intelligence (AI) methods in optical networks: A comprehensive survey
... ratio of the number of lost bursts to the total number of transmitted bursts – is commonly used for the performance measurement of OBS network ...terms of computation ...neural ... See full document
15
Networks of polarized evolutionary processors are computationally complete
... way of defining halting words is equivalent t o t h a t in [20], in t h e sense t h a t there exists a bijection between t h e valid c o m p u t a t i o n s obtained in each of these two ... See full document
12
Melomics: A Case-Study of AI in Spain
... many of which have computer science departments that host AI-related research ...advancement of AI since then. Along with several other societies and communities of interest, it promotes various ... See full document
5
Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.
... SELF-ORGANIZING ROUTING ALGORITHM FORWIRELESS SENSORS NETWORKS (WSN) USING ANT COLONY OPTIMIZATION (ACÓ) WITH TINYOS.. Nuria Gómez Blas, Luis F.[r] ... See full document
10
Cheminformatic models to predict binding affinities to human serum albumin
... forms of the QSAR equations, so GFA appears to be the appropriate choice for this ...interpretation of the model in physical ...other optimization algorithms, like neural networks; when ... See full document
9
On the possibility to design evolutionary algorithms with optimal equilibrium distribution . The case of simulated annealing
... flow of a program implementing the SA algorithm for the problem of maximising a function F taking real values over a set ...generation distribution, i.e. C(r,s) represents the probability of ... See full document
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