Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function

This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.

Planning of secondary distribution circuits through evolutionary algorithms

In this work, the planning of secondary distribution circuits is approached as a mixed integer nonlinear programming problem (MINLP). In order to solve this problem, a dedicated evolutionary algorithm (EA) is proposed. This algorithm uses a codification scheme, genetic operators, and control parameters, projected and managed to consider the specific characteristics of the secondary network planning. The codification scheme maps the possible solutions that satisfy the requirements in order to obtain an effective and low-cost projected system-the conductors' adequate dimensioning, load balancing among phases, and the transformer placed at the center of the secondary system loads. An effective algorithm for three-phase power flow is used as an auxiliary methodology of the EA for the calculation of the fitness function proposed for solutions of each topology. Results for two secondary distribution circuits are presented, whereas one presents radial topology and the other a weakly meshed topology. © 2005 IEEE.

A combinatorial approach for transmission expansion & reactive power planning

A metaheuristic technique for solving the short-term transmission network expansion and reactive power planning problems, at the same time, in regulated power systems using the AC model is presented. The problem is solved using a real genetic algorithm (RGA). For each topology proposed by RGA an indicator is employed to identify the weak buses for new reactive power sources allocation. The fitness function is calculated using the cost of each configuration as well as constraints deviation of an AC optimal power flow (OPF) in which the minimum reactive generation of new reactive sources and the active power losses are objectives. With allocation of reactive power sources at load buses, the circuit capacity increases and the cost of installation could be decreased. The method is tested in a well known test system, presenting good results when compared with other approaches. © 2011 IEEE.

A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest

Besides optimizing classifier predictive performance and addressing the curse of the dimensionality problem, feature selection techniques support a classification model as simple as possible. In this paper, we present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the fitness function to be maximized. Moreover, we present a methodology to better estimate the quality of the reduced feature set. Experiments conducted over six public datasets demonstrated that the proposed approach provides statistically significant more compact sets and, in some cases, it can indeed improve the classification effectiveness. © 2013 Elsevier Ltd. All rights reserved.

Detecção de falhas estruturais usando sensores e atuadores piezelétricos e algoritmos genéticos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Cardiorespiratory fitness, but not central obesity or C-reactive protein, is related to liver function in obese children

Nonalcoholic fatty liver disease (NAFLD) is one of the most frequent complications associated with excess adiposity. Its pathogenesis is complex and there are multiple factors that may contribute to it. AIM: To analyze whether cardiorespiratory ftness (CRF), waist circumference (WC), and C-reactive protein (CRP) are associated with alanine aminotransferase (ALT) in children with obesity. METHODS: 79 overweight/obese children of both genders, 11-13 year-olds, with abnormal serum ALT from Porto public schools comprised the sample. Measurements included CRF (20-m Shuttle Run Test), WC (NHANES protocol), CRP and ALT (Cholestech LDX analyzer). Logistic regression adjusted for gender, maturation, and weight with ALT levels as dependent variable (risk vs. non risk), and WC (risk vs. non risk), CRP (risk vs. non risk), and CRF (fit vs. unfit) as independent variables. Level of significance was set at 95%. RESULTS: Logistic regression showed that obese fit children were less likely to have abnormal ALT values (OR=.031) CONCLUSION: In obese children, higher cardiovascular fitness appears to reduce the chance of decreased liver function. © 2013 Human Kinetics, Inc.

Partitioning the relative fitness effects of diet and trophic morphology in the threespine stickleback

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Activation function study for wavelet network

The main purpose of this paper is to investigate theoretically and experimentally the use of family of Polynomial Powers of the Sigmoid (PPS) Function Networks applied in speech signal representation and function approximation. This paper carries out practical investigations in terms of approximation fitness (LSE), time consuming (CPU Time), computational complexity (FLOP) and representation power (Number of Activation Function) for different PPS activation functions. We expected that different activation functions can provide performance variations and further investigations will guide us towards a class of mappings associating the best activation function to solve a class of problems under certain criteria.