Thanks to their inherent properties, probabilistic graphical models are one of the prime
candidates for machine learning and decision making tasks especially in uncertain domains …

Mathematical models are used for simulating the electrochemical phenomena of proton-
exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision …

This paper presents an optimized design of a cable driven parallel manipulator which is
intended in rehabilitation or exercise of patients with shoulder problems like illness …

Fitness modeling has received growing interest from the evolutionary computation
community in recent years. With a fitness model, one can improve evolutionary algorithm …

In this paper, a method for concurrent optimum design of a complex parallel manipulator is
introduced. The manipulator is a three-degree-of-freedom mechanism used as a walking …

Topological shape optimization consists in finding the optimal shape of a mechanical
structure by means of a process for removing or inserting new holes and structural elements …

The covariance matrix adaptation evolution strategy (CMA-ES) is one of the state-of-the-art
evolutionary algorithms for optimization problems with continuous representation. It has …

Selection plays an important role in estimation of distribution algorithms. It determines the
solutions that will be modeled to represent the promising areas of the search space. There is …

Message passing algorithms (MPAs) have been traditionally used as an inference method in
probabilistic graphical models. Some MPA variants have recently been introduced in the …

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