Multiobjective Planning of Recloser Based Protection Systems - amazonia.fiocruz.br

Multiobjective Planning of Recloser Based Protection Systems Video

Multi-Objective Problems

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The dynamic construction site layout planning DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP for Nondeterministic Polynomial time -hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. The results indicate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process. Multiobjective Planning of Recloser Based Protection Systems

Try your query at:. An evolution based path planning algorithm for autonomous motion of a UAV through uncertain environments by David Rathbun, Ph. Adaptive and intelligent on-board path planning is a Systeks part of a fully autonomous UAV. In controlled airspace, such a UAV would have to interact with other vehicles moving though its environment.

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The locations of obstacles other vehicles that form obstructions in the environment may only Reclpser Abstract - Cited by 25 1 self - Add to MetaCart from those that would be favored in a purely deterministic environment. In this paper, we consider the application of evolution-based path planning to the motion of an unmanned air vehicle UAV through a field of obstacles at uncertain locations. We begin with the static form of the EA algorithm.

ACM, Abstract There are many methods for detecting and mitigating software errors but few generic methods for automatically repairing errors once they are discovered.

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This paper highlights recent work combining program analysis methods with evolutionary computation to automatically repair bugs in off-th Abstract - Cited by 34 5 self - Add to MetaCart typical software project. In Multiobjective Planning of Recloser Based Protection Systems paper, we describe how to combine this problem by combining program analysis methods with evolutionary computation to automatically repair bugs in off-the-shelf legacy C programs. Genetic programming GP is a computational method inspired by biological evolution which. Driankov and A. This paper presents an evolutionary learning algorithm to facilitate the design of fuzzy controllers for mobile robots. It discusses the concepts, feasibility, benefits and limitations of current evolutionary techniques for fuzzy rule discovery and tuning.

We propose an evolution strategy that opt Abstract - Cited by 1 0 self - Add to MetaCart. We propose an evolution strategy. Abstract: In order to reduce the memory footprint and energy consumption of embedded microcontroller in mobile robot, the concise differential evolution algorithm based on chaotic local search CDE-CLS is proposed for online optimization of recurrent fuzzy neural network RFNN controller in robot Abstract - Add to MetaCart Abstract: In order to reduce the memory footprint and energy consumption of embedded microcontroller in mobile robot, the concise differential evolution algorithm based on chaotic local search CDE-CLS is proposed for online optimization of recurrent fuzzy neural network RFNN controller in robot.

Sin, James N. Liu This paper outlines a comparative investigation check this out optimization using the integration of case based reasoning and neural network with the adoption of fuzzy clustering.

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In this integrated model, case based reasoning is applied to build the case profiles from various forms of data set that are use Abstract - Add to MetaCart control ru les. Fuzzy clustering is applied to the data analysis and adaptive gradient learning algorithms with various network architectures are studied. Previous results Liu and Sin indicate that the algorithm Multionjective combining case based reasoning and time lagge d recurrent network can generate. Laroque, J. Himmelspach, R.]