Recent electron microscopy work on rat olfactory system anatomy suggests a structural basis for grouping input stimuli before processing to classify odors. For a simulated nose, the number of inputs per group is a des...
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In this paper, we introduce and explore a novel Virtual Reality musical interaction system (named REVOLVE) that utilises a user-guided evolutionary algorithm to personalise musical instruments to users’ individual pr...
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When tackling constrained multi-objective optimization problems (CMOPs), especially problems with complex feasible areas, it is challenging for handling both objective optimization and constraint satisfaction. To reme...
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At present, many large and medium-sized cities in China are accelerating the construction of urban rail transit. The contradiction between urban transportation capacity and traffic volume has become increasingly promi...
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Feature construction represents a crucial data preprocessing technique in machine learning applications because it ensures the creation of new informative features from the original ones. This fact leads to the improv...
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In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master-slave structure and the migration is ...
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ISBN:
(纸本)9781605581309
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master-slave structure and the migration is centralized. In the model a basic evolutionary algorithm (EA) runs which is a hybrid, steady-state EA. The basic EA uses a new mutation operator that is composed of two parts and based on a modified version of an explicit collective memory method (EC-memory), the Virtual Loser [2].We tested our island model on the benchmark problems from the OR-Library. Comparing the results with other heuristic methods, we can conclude that our algorithm is highly effective in solving large instances of the BQP;it has a high probability of finding the best-known solutions.
The design optimization of wings for supersonic transport by means of Multiobjective evolutionary algorithms is presented. Three objective functions are first considered to minimize the drag for transonic cruise, the ...
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This work describes the use of a weighted ensemble of neural network classifiers for adaptive learning. We train the neural networks by means of a quantum-inspired evolutionary algorithm (QIEA). The QIEA is also used ...
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This paper proposes an approach based on the use of Cellular evolutionary Strategies (CES) and Interval Arithmetic (IA) as an alternative technique to obtain robust system design. CES are an approach that combines the...
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This work discusses the use of evolutionary computation for an automated player of a real-time strategic tactics game in which assets are assigned to targets and threats belonging to the opposing team. Strategy games ...
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ISBN:
(纸本)1424404649
This work discusses the use of evolutionary computation for an automated player of a real-time strategic tactics game in which assets are assigned to targets and threats belonging to the opposing team. Strategy games such as this are essentially a series of asset allocation problems to which evolutionary algorithms are particularly adept. This game contains a significant coupling affect between the assets assigned to targets and those assigned to threats. The effort considers targets and threats in a non-spatiotemporal framework to evaluate the proposed approach. In addition, the architecture that supports the implemented evolutionary search algorithm is also discussed.
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