The performance of Vis-NIR techniques combined with variable select by a simple modifiedparticleswarmoptimization (PSO) algorithm for the determination of four quality parameters in soy sauce was evaluated. Compare...
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The performance of Vis-NIR techniques combined with variable select by a simple modifiedparticleswarmoptimization (PSO) algorithm for the determination of four quality parameters in soy sauce was evaluated. Compared with full-spectral support vector machine regression (Full-SVMR) and SVMR based on competitive adaptive reweighted sampling (CARS-SVM) method, the application of PSO wavelength selection provided a notably improved SVM regression model. The root-mean-square error of amino acid nitrogen, salt, total acid content, and color ratio obtained by PSO-SVMR are 0.0075 g/100 ml, 0.2176 g/100 ml, 0.0077 g/100 ml, and 0.0506 in predicted sets, respectively. The correlation coefficients of predicted sets obtained by PSO-SVMR reached 0.9997, 0.9462, 0.9996, and 0.9998, respectively. Meanwhile, a classification study constructed with principal component analysis and SVM classification model based on the feature wavelengths selected by PSO shows that Vis-NIR spectra can be used to classify soy sauce according to their brands and quality. The result showed that the Vis-NIR spectroscopy technique based on PSO wavelength selection has high potential to predict the quality parameters in a nondestructive way. This analytical tool may also contribute to the detection of fraud and mislabeling in the soy sauce market and certainly contribute to improvement in quality and reliability of the soy sauce market.
Management of plug-in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimu...
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Management of plug-in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimulate issues such as increase in peak load, power loss, and voltage deviation. Addressing the aforementioned issues by incorporating distinct mobility patterns together will develop an attractive energy management. In this paper, suitable location of the charging station is presented for a novel 2-area distribution system following distinct mobility patterns. A comprehensive study by considering the optimal, midst, and unfit site for placing the charging station is incorporated. For managing the charging sequence of PHEVs, a meta-heuristic solving tool is developed. The main contribution of this programming model is its ability to schedule the vehicles simultaneously in both the areas. The efficiency of the proposed energy management framework is evaluated on the IEEE 33-bus and IEEE 69-bus distribution systems. The test system is subjected to different scenarios for demonstrating the superior performance of the proposed solving tool in satisfying the convenience of vehicle owner along with reducing the peak demand. The results show that charging at low electricity price period and discharging at high electricity price period enables the minimum operational cost.
In order to solve the challenging coverage problem that the long term evolution（ LTE） networks are facing, a coverage optimization scheme by adjusting the antenna tilt angle（ ATA） of evolved Node B（ e NB） is pro...
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In order to solve the challenging coverage problem that the long term evolution（ LTE） networks are facing, a coverage optimization scheme by adjusting the antenna tilt angle（ ATA） of evolved Node B（ e NB） is proposed based on the modifiedparticleswarmoptimization（ MPSO） *** number of mobile stations（ MSs） served by e NBs, which is obtained based on the reference signal received power（RSRP） measured from the MS, is used as the metric for coverage optimization, and the coverage problem is optimized by maximizing the number of served MSs. In the MPSO algorithm, a swarm of particles known as the set of ATAs is available; the fitness function is defined as the total number of the served MSs; and the evolution velocity corresponds to the ATAs adjustment scale for each iteration cycle. Simulation results showthat compared with the fixed ATA, the number of served MSs by e NBs is significantly increased by 7. 2%, the quality of the received signal is considerably improved by 20 d Bm, and, particularly, the system throughput is also effectively increased by 55 Mbit / s.
The paper proposes a modified particle swarm optimization algorithm (MPSO) for online tuning to the fuzzy controller of power system stabilizer (PSS). The hybrid fuzzy controller combines concepts from fuzzy systems a...
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ISBN:
(纸本)9781538609903
The paper proposes a modified particle swarm optimization algorithm (MPSO) for online tuning to the fuzzy controller of power system stabilizer (PSS). The hybrid fuzzy controller combines concepts from fuzzy systems and particleswarmoptimization to produce powerful system controllers that are used for adaptive control. Two synchronous generators fitted with a PSS and are connected via double transmission lines will be the system under study. Three types of PSS controllers such as Conventional lead-lag PSS (CPSS), Static Fuzzy Logic Controller (SFLC) and online tuning Fuzzy Logic Controller based on PSO algorithm will be considered. The modified PSO algorithm used to adjust the fuzzy set parameters of each Fuzzy Logic Controller (FLC-PSO) online. The speed error and the change of error are the input vector, and the stabilizing signal is the output of both fuzzy logic controller (FLC). The FLC controllers will be tested under different disturbances for a wide-range of operating points. The computation time and the complexity of the fuzzy controller are reduced. The simulation results ensure the effectiveness of the proposed FLC-PSO controller for achieving the good dynamic response of the system under study.
The tremendous use of hazardous materials has promoted the economic development, which also brings about a growing risk causing a widespread concern. In-this work, we consider a location-scheduling problem on hazardou...
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The tremendous use of hazardous materials has promoted the economic development, which also brings about a growing risk causing a widespread concern. In-this work, we consider a location-scheduling problem on hazardous materials transportation under the assumption that transportation risks are time-dependent fuzzy random variables. First, we formulate a scheduling optimization model and design a fuzzy random simulation based genetic algorithm to optimize the departure time and dwell times for each depot-customer pair. Then we establish an expected value model and design a modified particle swarm optimization algorithm to minimize the en route risks and site risks. Finally, numerical examples are given to illustrate the effectiveness of the proposed models and algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
A staircase modulation strategy based on modifiedparticleswarmoptimization (MPSO) algorithm is presented in this paper to solve the key problem of staircase modulation in modular multilevel converter. Firstly, each...
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ISBN:
(纸本)9781479943159
A staircase modulation strategy based on modifiedparticleswarmoptimization (MPSO) algorithm is presented in this paper to solve the key problem of staircase modulation in modular multilevel converter. Firstly, each harmonic of output voltage is analyzed, and the object function is optimized. Then the modified MPSO, which has the merit of high accuracy, was adopted for calculating the switching angles. Considering the voltage balancing requirements, the square wave pulses rotation method and staircase modulation strategy are combined together to reduce the voltage ripple of floating capacitor. Voltage balancing control is achieved without extra voltage controls. Both the simulation and experimental results of five-level MMC prototype verified the feasibility and effectiveness of the proposed strategy.
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