Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is...
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Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined;the model is based on cross correlation (CC) analysis and a support vector regression (SVR) model that is coupled with brainstorm optimization (BSO) and cuckoo search (CS) algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.
The authors describe how novel sensors and control algorithmsembedded in today's domestic appliances make them smart enough toestimate the size and dirtiness of a load of clothes tossed in a washeror to determine ...
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The authors describe how novel sensors and control algorithmsembedded in today's domestic appliances make them smart enough toestimate the size and dirtiness of a load of clothes tossed in a washeror to determine whether water in a pot on the stove is boiling. Theyargue that, as semiconductor costs come down, such appliances will geteven smarter
This paper describes a novel method to enhance underwater images by image dehazing. Scattering and color change are two major problems of distortion for underwater imaging. Scattering is caused by large suspended part...
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This paper describes a novel method to enhance underwater images by image dehazing. Scattering and color change are two major problems of distortion for underwater imaging. Scattering is caused by large suspended particles, such as turbid water which contains abundant particles. Color change or color distortion corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths, rendering ambient underwater environments dominated by a bluish tone. Our key contributions are proposed a new underwater model to compensate the attenuation discrepancy along the propagation path, and proposed a fast joint trigonometric filtering dehazing algorithm. The enhanced images are characterized by reduced noised level, better exposedness of the dark regions, improved global contrast while the finest details and edges are enhanced significantly. In addition, our method is comparable to higher quality than the state-of-the-art methods by assuming in the latest image evaluation systems. (C) 2013 Elsevier Ltd. All rights reserved.
Total variation method has been widely used in image processing, however, it produces undesirable staircase effect. Recently, the two-step method has been used to alleviate the staircase effect successfully. Combined ...
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Total variation method has been widely used in image processing, however, it produces undesirable staircase effect. Recently, the two-step method has been used to alleviate the staircase effect successfully. Combined with a new vector field and an edge indicator function, a novel variational model is proposed in this paper. Unlike the two-step method, the proposed model contains only one energy functional, that is to say, the new vector field and the reconstructed image are interwoven. Due to using the information of the restored image fully, the new vector field is more accurate than the normal vector field, and the reconstructed image is also better than that in the two-step method. To solve the new model, we design a primal-dual method to simulate the minimization problem. The numerical experiments show that the new model can obtain significant improvement not only in noise removal but also in avoiding staircase effect. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the...
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The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the improvement of power loss and voltage profile can be the salient benefits. However, studies show that improper placement and size of energy storage system (ESS) lead to undesired power loss and the risk of voltage stability, especially in the case of high renewable energy penetration. To solve the problem, this paper sets up a microgrid based on IEEE 34-bus distribution system which consists of wind power generation system, photovoltaic generation system, diesel generation system, and energy storage system associated with various types of load. Furthermore, the particle swarm optimization (PSO) algorithm is proposed in the paper to minimize the power loss and improve the system voltage profiles by optimally managing the different sorts of distributed generations under consideration of the worst condition of renewable energy production. The established IEEE 34-bus system is adopted to perform case studies. The detailed simulation results for each case clearly demonstrate the necessity of optimal management of the system operation and the effectiveness of the proposed method.
To avoid immature convergence and tune the selection pressure in the differential evolution (DE) algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS) or ccDE is p...
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To avoid immature convergence and tune the selection pressure in the differential evolution (DE) algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS) or ccDE is proposed. To balance the exploration and exploitation tradeoff of differential evolution, the interaction among individuals is limited in cellular neighbors instead of controlling parameters in the canonical DE. To improve the optimizing performance of DE, the CLS helps by exploring a large region to avoid immature convergence in the early evolutionary stage and exploiting a small region to refine the final solutions in the later evolutionary stage. What is more, to improve the convergence characteristics and maintain the population diversity, the binomial crossover operator in the canonical DE may be instead by the orthogonal crossover operator without crossover rate. The performance of ccDE is widely evaluated on a set of 14 bound constrained numerical optimization problems compared with the canonical DE and several DE variants. The simulation results show that ccDE has better performances in terms of convergence rate and solution accuracy than other optimizers.
Attempts to find a simple and quick procedure on the microcomputer for scheduling activities of a constrained multiple resource single project network that would minimize project duration. Combination of simple heuris...
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Attempts to find a simple and quick procedure on the microcomputer for scheduling activities of a constrained multiple resource single project network that would minimize project duration. Combination of simple heuristics; Procedure for determining the combination of heuristics; Development of a computer algorithm.
Practical welding control systems require durable/compact sensors to sense the welding process and appropriate control algorithms to produce smooth welds. A novel arc welding sensor referred to as nontransferred plasm...
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Practical welding control systems require durable/compact sensors to sense the welding process and appropriate control algorithms to produce smooth welds. A novel arc welding sensor referred to as nontransferred plasma charge sensor which requires no additional attachment to the torch, has been proved to be reliable for weld pool surface sensing. Aiming at eliminating the effect of manufacturing conditions on the sensor performance, this paper proposes two simple yet effective methods. Specifically, reference signals are sampled either from the bottom or the top surface of the work-piece and used to define relative signals, which can measure the depth of the weld pool with better accuracy. Using improved sensing methods, two groups of welding control experiments, keyhole plasma arc welding and all-position pipe welding, have been conducted, and the effectiveness of the developed sensing/control systems in producing quality welds under various conditions is verified.
As the deployment of high-speed fiber transmission systems has been accelerated, they are widely recognized as a firm infrastructure of our information society. Under this circumstance, the importance of network survi...
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As the deployment of high-speed fiber transmission systems has been accelerated, they are widely recognized as a firm infrastructure of our information society. Under this circumstance, the importance of network survivability has been increasing rapidly in these days. In SONET, the self-healing networks have been highlighted as one of the most advanced mechanisms to realize SONET survivable networks. Several schemes have been proposed and studied actively due to a rapid progress on the development of highly intelligent NE's. Among them in this paper, a DCS based distributed self-healing network is discussed from a viewpoint of its control algorithms. Specifically, our self-healing algorithm called TRANS is explained in detail, which possesses such desirable features as providing fast and flexible restoration with line and path level restoration applied to an individual STS-1 channel, capability to handle multiple and even node failures, and so on. Both software simulation and hardware experiment verify that TRANS works properly in a real distributed environment, the result of which is shown in the paper. In addition, the combined use of TRANS and the ring restoration control is proposed taking into account the use in a practical SONET.
We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed framework, low-cost static cameras are deployed to cover a large region, moving targets are detect...
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We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed framework, low-cost static cameras are deployed to cover a large region, moving targets are detected and then tracked using corresponding algorithms, target positions are estimated by making use of the geometrical relationships among those cameras after calibrating those cameras, and finally, for each target, its position estimates obtained from different cameras are unified into the world coordinate system. This system can function as complementary positioning information sources to realize moving target positioning in indoor or outdoor environments when global navigation satellite system (GNSS) signals are unavailable. The experiments are carried out using practical indoor and outdoor environment data, and the experimental results show that the systematic framework and inclusive algorithms are both effective and efficient.
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