Traffic information is so far less than the number of OD variables, that it is difficult to obtain the satisfactory solution. In this paper, a method based on Quantum behaved Particle Swarm Optimization (QPSO) algorithm is developed to obtain the global optimal solution. It designs the method based on QPSO algorithm to solve the OD matrix prediction model, lists the detailed steps and points ou...

To achieve sustainable development and improve market competitiveness, many manufacturers are transforming from traditional product manufacturing to service manufacturing. In this trend, the system (PSS) has become mainstream of supply satisfy customers with individualized products combinations. The diversified customer requirements can be realized by PSS configuration based on modular design. ...

Short-term power prediction of the photovoltaic system is one of the effective means to reduce the adverse effects of photovoltaic power on the grid. Since the efficiency of the traditional support vector machine (SVM) prediction method is low, this paper proposes the SVM based on the parameter optimization method of quantum particle swarm optimization (QPSO), and then apply into the power shor...

The stock market is very volatile, so the change of price also widely concerned by investors. In this paper, a new forecasting model based on Quantum Particle Swarm Optimization(QPSO) , Bee Colony Optimization Algorithm(QABC) and Fruit Fly Algorithm (QFOA) proposed. three methods all use BP neural network to adjust parameters particle swarm, bee colony Drosophila reach optimal parameters. Takin...

Cognitive radio (CR) is an innovative and contemporary technology that has been making effort to overcome the problems of bandwidth reduction by rising usage mobile cellular connections. The reallocation distribution channels a fundamental characteristic networks (CMN) exploit consumption CMS. Meanwhile, throughput maximization might lead higher power utilization, spectrum sensing system must t...

This paper proposes a combination of particle swarm optimization (PSO) and Q-value based safe reinforcement learning scheme for neuro-fuzzy systems (NFS). The proposed Q-value based particle swarm optimization (QPSO) fulfills PSO-based NFS with reinforcement learning; that is, it provides PSO-based NFS an alternative to learn optimal control policies under environments where only weak reinforce...

A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. F...

Extracting the information with biological significance in amounts of gene expression data is an important research direction. Clustering algorithm in this area has been increasingly widely applied. According to the characteristic of gene expression data, the improved projection pursuit cluster model was introduced in this area and Quantum-behaved Particle Swarm Optimization(QPSO) was put forwa...

In this paper, a novel CMOQPSO algorithm is proposed, in which cultural evolution mechanism is introduced into quantum-behaved particle swarm optimization (QPSO) to solve multiobjective environmental/economic dispatch (EED) problems. There are growing concerns about the ability of QPSO to handle multiobjective optimization problems. Two important issues in extending QPSO to multiobjective conte...