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The recognition of tire sidewall text refers to the technology that automatically detects and extracts textual information on tire sidewalls in dark background. This article explores the importance of tire sidewall text recognition and proposes a ...

The incentive for using Evolutionary Algorithms (EAs) for the automated optimization and training of deep neural networks (DNNs), a process referred to as neuroevolution, has gained momentum in recent years. The configuration and training of these ...

One of the main tasks in agriculture is deciding which crop should be planted on which field. Agricultural companies often cultivate dozens of crops on hundreds of fields, making this problem extremely computationally complex. It was solved within ...

Evolutionary multi-criterion optimization (EMO) algorithms emphasize non-dominated and less crowded solutions in a population iteratively until the population converges close to the Pareto optimal set. During the search process, non-dominated solutions ...

When data mining techniques are applied to discover useful knowledge behind a large data collection, they are often required to preserve some confidential information, such as sensitive frequent itemsets, rules and so on. A feasible way to ensure the ...

Started during 1993-95 with three different algorithms, evolutionary multi-objective optimization (EMO) has come a long way in a quick time to establish itself as a useful field of research and application. Till to date, there exist numerous textbooks ...

It is possible for the μ+1-SMS-EMOA to decrease in dominated hypervolume w.r.t. a global reference point. We study the influence of SMS-EMOA parameter settings on number and amount of the observed decreases. We show that the number of decreases drop and ...

Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and ...

In this paper, we propose a hybrid reference-point based evolutionary multi-objective optimization (EMO) algorithm coupled with the classical SQP procedure for solving constrained single-objective optimization problems. The reference point based EMO ...

In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMOprocedure to develop an algorithm for finding a single preferred solution in a multi-objective ...