Search

Open Vehicle Routing Problem with Time Dependent Travel Time (OVRPTD) is different from most variants of vehilce routing problems from the liteture in that the vehicle dosen't return to the depot after serving the last customer and the travle time is time dependent. The travle time is presented by a continuous dynamic network time dependent function. Particle Swarm Optimization with self-adaptive inertia weight is presented. Each particle regulates its inertia weight according to the corresponding position with itself and the best particle in the population. Different updating rules are applied to the excellence particles and the inferior particles. For the excellence particles, compute their information entropy after server iterations, and update their position according to the new position updating function. And for the inferior particles, record them in the bulletin board, then after several iteration, use the new particles displace the inferior according the appearance frequency in the board. In the experiment, the influence of the population, iteration, inertia weight for the optimization result is discussed. By the experiment, give the field of the parameter. Compare the particle swarm optimization with other algorithms by the benchmark. The result shows the algorithm in the paper is the efficiency for the OVRPTD.

Protocol with QoS guarantee in unidirectional MANET is very important. Many of the classical routing protocols are put forward on the basis of two-way communication. While there exits unidirectional link because of differences in transmission power in each terminals as well as environmental factors such as topography and so on. This paper studies and applies the shortest path method based on graph theory and advances a new routing protocol with QoS guarantee in unidirectional MANET. In order to analyze its performance, adopt MANET to simulate the new routing model and compare it with DSR.

Privacy area protection has become more important than before in networked video surveillance. In this paper, we address privacy area protection related issues. First, the characteristics of security camera with pan/tilt rotation mechanism are introduced and the privacy problems of video surveillance in public areas are analyzed. Then, a new method of protecting privacy areas is proposed to automatically adapt the panning rotation and tilting rotation of security camera. This method contains two steps to calculate the masked area matrix from predetermined privacy area matrix and some static/dynamic basic parameters. Experimental results have shown that the proposed method could work well in real-systems and protect the privacy areas efficiently.

In order to reduce the local environment impact, the improved methods of optimal scheduling small hydropower are discussed and the sustainability optimal scheduling models which composed of optimal objectives and constraints are presented. The controlled reservoir releases for hydropower generation which based on float coding is used as the decision variable of the model and the reserved minimum flow and reservoir water level as special constraints. The controlled reservoir water level compared with maximal energy output during the period of dispatching is considered as objective. An improved PSO, resilient particle swarm optimization (RPSO), is adopted to the optimization. In RPSO, the velocity of a particle is not dependent on the size of distance between the individual and the optimal particle but only dependent on its direction. An adaptive scheme is adopted to adjust the magnitude of the velocity resiliently. A simulation operation of RPSO Matlab program for a factual small hydropower plant show that the sustainability optimum scheduling models and the technology based RPSO is viable and efficient. RPSO performance was compared with PSO and APSO on the same case, the results show that RPSO performed better.

The cooperation mode based on fractal-agent of the networked cooperative manufacturing system is introduced. According to the task executing principle of the fractal-agent, the dynamic task is bound to the corresponding dynamic role. It leads to raise the fractal-agent based Web access control approach, security policy and the relating access control matrix. Furthermore, the approach is carried out to enable the secure access, administration and control of the cooperative manufacturing system. The experimental results show that the research can meet the requirement of the Web access security of the enterprise cooperative manufacturing system.

To improve ATM network survivability level, a discrete Hopfield neural network algorithm with transient chaos for VP routing in ATM network was put forward. The computational energy function of VP routing and the motion equation of the discrete Hopfield neural network with transient chaos were also given. Compared with the VP routing algorithms exited, the simulation results show that it is both faster and more effective to achieve VP routing.

Having considered all the constraints of the job-shop scheduling problem (JSP), we present a new computational energy function of Hopfield neural networks for JSP. By introducing transient chaos and time-variant gain, an improved method to solve JSP by a neural network model with transient chaos is proposed, which can avoid Hopfield neural networks being sucked into local minima. The simulation results show that the modified method not only has the ability of searching for the global minimum, but can also converge to minimum quickly. More importantly, it can keep the steady output of neural networks as a feasible solution for JSP.

At present, wastewater treatment quality parameters cannot be detected on-line. In this paper, the soft-sensing method based on artificial neural networks is proposed in order to resolve this problem. The wastewater treatment technique is analyzed systematically. ORP, DO, PH and MLSS which can be detected on-line are taken as the secondary variables. BOD, COD, N and P which cannot be detected on-line are taken as the primary variables. The BP neural network for soft-sensing is proposed and trained using the testing data of the practical treatment process. The simulation results show that the soft-sensing system of wastewater treatment based on the BP neural network can correctly estimate the quality parameters in real time. Thus, the system can be accommodated to the changes of the environment and implement the real time control of wastewater treatment.

In this paper, the greenhouse climate model based on adaptive fuzzy logic system is presented. Greenhouse climate system is a nonlinear system with the various climate factors being coupled. Due to its capability to handle both numerical data and linguistic information, it is feasible to apply adaptive fuzzy logic system to model for greenhouse climate, and then provide prediction for greenhouse climate control.