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In the vehicle routing problem (VRP), it is usually difficult to confederate the cargo and arrange vehicles path. Due to performance reasons, the traditional shortest path algorithm can not be applied to the large scale of VRP. On the basis of the VRP mathematical model, this paper constructs a mixed climbing particle swarm algorithms to solve the problem. First, through coding, the VRP problem is...
The coaxial two-mirror telescope consists of two mirrors facing each other. Classical two-mirror arrangements are Gregorian and Cassegrain. These systems are usually applied to space telescopes and often have optical baffles to prevent stray light from entering the focal plane. The optical baffles consist of concentric rings suspended between the secondary and the primary mirror. The secondary baffle...
In this paper, we propose a novel proportional fair scheduling algorithm for MAC-layer sensing in the cognitive radio networks (CRNs). According to the secondary user (SU) channel state information and primary user (PU) traffic patterns, the SUs are adaptively scheduled to carry out sensing and transmission in different channels. Moreover, we jointly consider multiple important design factors in the...
Effective image parsing needs a representation that is both selective (to inter-class variations) and invariant (to intra-class variations). CodeBook from bag-of-visual-words representation addresses the invariance, and part-based models can potentially address the selectivity. However, existing part-based approaches either require expensive manual object-level labeling or make strong assumptions...
A sound transmission network ensures the secure and economical operation of power system. Several large- scale blackouts in the world have attracted attentions to dynamic and static security of transmission expansion planning. This paper points out that the security risk of transmission system, expressed by quantitative indices, should be considered in the objective function. In order to ensure a...
The huge increase of hyperspectral data dimensionality and information redundancy has brought high computational cost as well as the over-fitting risk of classification. In this paper, we present an automatic band selection and classification method based on a novel wrapper Multiple Improved particle swarm cooperative optimization and support vector machine model (MIPSO-SVM). The MIPSO-SVM model optimizes...
In this paper, a novel method for improving flexible neural tree is proposed to classify the leukemia cancer data. The hybrid flexible neural tree with pre-defined instruction sets can be created and evolved. The structure and parameter of hybrid flexible neural tree are optimized using probabilistic incremental program evolution (PIPE) and particle swarm optimization (PSO) algorithm. The experimental...
Three dimensional (3D) System-on-Chips (SoCs) that typically employ through-silicon vias (TSVs) as vertical interconnects, emerge as a promising solution to continue Moore's law. Whereas, it also brings challenging problems, one of which is the test wrapper chain design and optimization, especially for circuit-partitioned 3D SoCs in which scan chains can cross among layers. Test time is the primary...
Developing compressed sensing (CS) theory has been applied in radar imaging by exploiting the inherent sparsity of radar signal. In this paper, we develop a super resolution (SR) algorithm for formatting inverse synthetic aperture radar (ISAR) image with limited pulses. Assuming that the target scattering field follows an identical Laplace probability distribution, the approach converts the SR imaging...
Wind power flow optimization control system based on the supercapacitor and the battery can smooth the power fluctuation of wind power generation, enhance the capacity creditability and improve the power quality. Firstly, the overall topology and basic idea of wind power flow optimization and control system is analyzed. In the system, a bi-directional DC-DC converter is used to control and distribute...
An improved genetic algorithm (Fuzzy Adaptive Simulated Annealing Genetic Algorithm with Gradient direction, GFASAGA) will be proposed in this paper, whose global superlinear convergence properties was analyzed by means by Markov chain etc. Certain fuzzy aeroengine compressor guide vane controller parameters of the regulator were optimized by GFASAGA, standard genetic algorithm (SGA) and customized...
Locality-Sensitive Hashing (LSH) approximates nearest neighbors in high dimensions by projecting original data into low-dimensional subspaces. The basic idea is to hash data samples to ensure that the probability of collision is much higher for samples that are close to each other than for those that are far apart. However, by applying k random hashing functions on original data, LSH fails to find...
University examination timetabling problem is a complicated, multi-constraint combinatorial optimization problem. The current grouping genetic algorithm could get a better optimistic solution. Although the block encoding technique was applied in, the probabilities of crossover and mutation operation were still based on simple genetic algorithm. So the universality of this algorithm is not very well...
A design method for bandwidth-efficient LDPC coded modulation for 22m-QAM constellations at rate (2m - 1)/(2m) in complex AWGN is presented. A multi-edge-type parameterization is used to exploit the distinct bit-channel capacities unique to high-order modulation using LDPC structures. EXIT analysis is adapted to multi-edge by introducing multi-dimensional EXIT iterated-function system analysis. Under...
This paper examines the capacity of a time division duplex (TDD) multiple input single output (MISO) beamforming system with channel estimation error and delay over the time varying fading channel. In TDD system, the base station estimates the channel state information (CSI) at transmitter based on uplink pilots and then uses it to generate the beamforming vector in the downlink transmission. Because...
An optimal scheme on uplink pilot time interval (UPTI) to maximize average post-processing SNR (signal to noise ratio) is proposed in order to overcome the impact of channel estimation error and delay on a time division duplex (TDD) multiple input single output (MISO) beamforming system. In TDD system, the base station estimates the channel state information (CSI) at transmitter based on uplink pilots...
Hybrid power system (HPS) is the power system consists of renewable energy sources and traditional energy sources used together to increase system efficiency and reduce operation cost. Energy management is one of the main issues in operating the HPS, which needs to be optimized with respect to the current and future change in generation, demand, and market price, particularly for HPS with strong renewable...
Hybrid power system (HPS) is the power system consists of renewable energy sources and traditional energy sources used together to increase system efficiency and reduce operation cost. Energy management is one of the main issues in operating the HPS, which needs to be optimized with respect to the current and future change in generation, demand, and market price, particularly for HPS with strong renewable...
Multi-scale kernel function learning is a special case of multi-kernel learning, namely combines several multi-scale kernels. This approach is more flexible. It provides more comprehensive choice of scale than the mixed kernel learning. In this paper, the model's parameters of multi-scale Gaussian kernel were used as elementary particles. The parameters of multi-scale Gaussian kernel were global optimized...
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