Neural networks (NN) architectures can be effectively used to classify, forecast and recognize quantity of interest in, e.g., computer vision, machine translation, finance, etc. Concerning the financial framework, forecasting procedures are often used as a part of the decision making process in both trading and portfolio strategy optimization. Unfortunately training a NN is in general a challen...

In this article, multiple-product PVRP with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. A mathematical formulation was provided for this problem. Each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. To solve the problem, two meta-heuristic methods...

In order to overcome the defects of the slow convergence rate of the traditional Genetic Algorithm and basic Particle Swarm Optimization drops into local optimum easily, an improved Particle Swarm Optimization algorithm based on hybrid algorithm is proposed and applied to the signal detection for MIMO-OFDM system. The algorithm optimizes the basic Particle Swarm Optimization algorithm and some ...

This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-O...

Agent Swarm Optimization (ASO) is a generalization of Particle Swarm Optimization (PSO) orientated towards distributed artificial intelligence, taking as a base the concept of multi-agent systems. It is aimed at supporting decision-making processes by solving either single or multi-objective optimization problems. ASO offers a common framework for the plurality of co-existent population-based a...

-Content-based image retrieval (CBIR) is a widely researched area, with various techniques proposed in literature for feature extraction, classification and retrieval. But, when database size increases, overall retrieval performance deteriorates significantly. Features in pattern recognition are individual measurable heuristic properties of the image under observation. Choosing discriminating/i...

In order to optimize the spectrum resource allocation in the orthogonal frequency division multiplexing system and minimize the transmitted power, this paper proposed a modified basic particle swarm optimization algorithm to allocate the subcarriers and bits of the orthogonal frequency division multiplexing system. The algorithm uses the average individual extreme value instead of individual ex...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...