The conventional parameter optimisation of PID controller is easy to produce surge and big overshoot, and therefore heuristics such as genetic algorithm (GA), particle swarm optimisation (PSO) are employed to enhance the capability of traditional techniques. But the major problem of these algorithms is that they may be trapped in the local optima of the objective and lead to poor performance. I...

In this paper, a novel feature extraction approach which can be referred to as moving window function capturing (MWFC) has been proposed to analyze signals of an electronic nose (E-nose) used for detecting types of infectious pathogens in rat wounds. Meanwhile, a quantum-behaved particle swarm optimization (QPSO) algorithm is implemented in conjunction with support vector machine (SVM) for real...

How to make the RFID reader have better coverage and improve the accuracy of transmitting information has always been the research direction. In this paper, the RFID reader individual is corresponded with particles in PSO. First of all, establish the optimization function by interfering with signals in the RFID network with distribution density of reader and data transmission load as the target...

In this paper, a methodology is presented for optimum shape design of double-layer grids subject to gravity and earthquake loadings. The design variables are the number of divisions in two directions, the height between two layers and the cross-sectional areas of the structural elements. The objective function is the weight of the structure and the design constraints are some limitations on str...

In this study, the Direction Of Departure (DOD) and Arrival (DOA) of signals detection for Multi-Input Multi-Output (MIMO) radar is discussed. A novel signal subspace reconstruction model to match obtained based on covariance matrix array output developed enhance performance DOD DOA detection. scheme, technology beamforming first introduced define an objective space in mathematics targets be de...

Network traffic flow prediction model is fundamental to the network performance evaluation and the design of network control scheme which is crucial for the success of high-speed networks. Aiming at shortcoming of the conventional network traffic time series prediction model and the problem that BP training algorithms easily plunge into local solution, a network traffic prediction model based o...

This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized ver...

The study of protein tertiary structure prediction is useful to protein function. This paper proposes a novel protein tertiary structural prediction approach based on flexible neural tree (FNT). In this approach, the approximate entropy and hydrophobicity pattern of a protein sequence are adopted to characterize the Pseudo-Amino Acid (PseAA) components as input. A novel quantum particle swarm o...