Adaptive Performance Optimization for Large-Scale Traffic Control Systems
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This paper presents a method to optimize two linear actuator configurations. The method is stochastic and combines a genetic algorithm (GA) and FEM (finite element method) model generated with the commercial software FEMM. The optimization is performed in ...
The paper presents an optimization design of an in-wheel BLDC motor for a kick scooter. The optimization is performed using a genetic optimization tool combined with a FEM commercial software. The new contributions of the paper are: (i) introduction of thr ...
Nowadays, the general trend towards to minimally invasive interventions is present in all the medical domains. For the surgical intervertebral spinal disc cutting or removal domain, it is particularly a necessity because the manual methods currently employ ...
The aim of this project is to integrate uncertainty analysis in a thermo-economic optimization framework to be used as decision making support in the design of energy systems.Tree comprehensive thermo-economic models of fuel cells systems have been develop ...
This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally-measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in ...
In high head dams, the kinetic energy at the spillway toe is very high and the tail-water depth available for energy dissipation is relatively small. Cascade stilling basins are energy dissipation systems for high head dams, the design of which is based on ...
This paper describes new optimization strategies that offer significant improvements in performance over existing methods for bridge-truss design. In this study, a real-world cost function that consists of costs on the weight of the truss and the number of ...
Discrete optimization is a difficult task common to many different areas in modern research. This type of optimization refers to problems where solution elements can assume one of several discrete values. The most basic form of discrete optimization is bin ...
We have developed a new derivative-free algorithm based on Radial Basis Functions (RBFs). Derivative-free optimization is an active field of research and several algorithms have been proposed recently. Problems of this nature in the industrial setting are ...