A mathematical model of electroslag remelting (ESR) process is established based on its technical features and dynamic characteristics. A new multivariable self-tuning proportional-integral-derivative (PID) controller tuned optimally by an improved particle swarm optimization (IPSO) algorithm is proposed to control the two-input/two-output (TITO) ESR process. An adaptive chaotic migration mutat...

The modern traffic control timing plan aims at raising transportation efficiency of vehicles by making full use of existing road resources. So we built a region traffic control model; its performance of model is measured by minimum average travel time of vehicles, its average delay model for single crossroad is derived from the revised HCM2000; and then it is transformed into objective function...

A novel optimization algorithm, called accelerated particle swarm optimization (APSO), is proposed to be used for dynamic spectrum sensing in cognitive radio networks. While modified swarm-based optimization algorithms focus on slight variations of the standard mathematical formulas, in APSO, the acceleration variable of the particles is also considered in the search space. We show that the pro...

This paper proposes a TSK-type Neuro-Fuzzy system tuned with a novel learning algorithm. The proposed algorithm used an improved version of the standard Particle Swarm Optimization algorithm, it employs several sub-swarms to explore the search space more efficiently. Each particle in a sub-swarm correct her position based on the best other positions, and the useful information is exchanged amon...

We propose an improved algorithm, for a multiswarm particle swarm optimization with transfer of the best particle called BMPSO. In the proposed algorithm, we introduce parasitism into the standard particle swarm algorithm (PSO) in order to balance exploration and exploitation, as well as enhancing the capacity for global search to solve nonlinear optimization problems. First, the best particle ...

In recent time, road traffic accidents are increased day by due to incremental growth in number of vehicles. Traffic also the crucial and important issue for achieving sustainable transportation development. One tasks is reduce design assessment policy. Many researchers consider accident developed prediction models measuring severity accidents. But accuracy one major issues. this work, an attem...

This paper proposes a novel optimization algorithm combined the mechanism of quantum evolutionary algorithm and real-coding method, called an improved quantum particle swarm optimization algorithm (IQPSO). Like the traditional particle swarm optimization, IQPSO is also characterized by position vector and velocity vector to implement the evolution process. However, the particle of IQPSO is divi...

Standard particle swarm optimization is easy to fall into local optimum and has the problem of low precision. To solve these problems, the paper proposes an effective approach, called particle swarm optimization based on multiple swarms and opposition-based learning, which divides swarm into two subswarms. The 1st sub-swarm employs PSO evolution model in order to hold the self-learning ability;...