检索结果-内蒙古大学图书馆

Improved wavelet neural network combined with particle swarm optimization algorithm and its application

Journal of Central South University of Technology 2006年第3期13卷 256-259页

作者：李翔杨尚东乞建勋杨淑霞 School of Business Administration North China Electric Power UniversityBeijing 102206China

An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function.

关键词： artificial neural network particle swarm optimization algorithm short-term load forecasting wavelet curse of dimensionality

来源：评论

学校读者我要写书评

暂无评论

Smart prediction for tunnel fire state evolution based on an improved fire simulation curve through particle swarm optimization algorithm

引用

FIRE SAFETY JOURNAL 2023年第1期136卷

作者： Liu, Xiaojiang Xu, Zhao-Dong Sun, Bin Liu, Xuanya Xu, Dajun Southeast Univ China Pakistan Belt & Rd Joint Lab Smart Disaster Nanjing 210096 Peoples R China Tianjin Fire Res Inst Minist Emergency Management Tianjin 300381 Peoples R China

Tunnel fires have received significant attention because they can cause large economic losses every year. To estimate the fire development and realize a prompt response to the fire disaster are thus crucial to tackle the above issue. Here, a smart prediction method for fire state evolution is developed based on an improved fire simulation curve through the particle swarm optimization algorithm. The improved fire simulation curve is established by supplementing the stable stage during the tunnel fire based on a fire curve proposed in 2002. Experimental results from a prototypical tunnel fire test indicate that the proposed method can effectively portray the behavior of a typical tunnel fire development. Moreover, it is accurate over a wide range of conditions, including different heat release rates, different measurement noises, different sampling intervals, and different prior durations. Particularly, the fluctuation range of estimation results is becoming larger with the increasing noise level. The influence of the sampling interval is mainly reflected in the calculation time. Prior duration is the most important factor of the prediction accuracy, the longer prior duration corresponds to the more precise results. 200s and 300s can be regarded as the critical duration by considering the estimation error of the whole-time domain and the preliminary stage, respectively. The proposed method has a broad application prospect, it can avoid complicated temperature spreading mechanisms, the additional workload for prior information, and the limitation of the specific fire scene.

关键词： Tunnel fire Fire state evolution particle swarm optimization algorithm Fire simulation curve Full-scale tests

来源：评论

学校读者我要写书评

暂无评论

An integrated energy system optimization strategy based on particle swarm optimization algorithm

引用

ENERGY REPORTS 2022年 8卷 679-691页

作者： Wu, Min Du, Pengcheng Jiang, Meihui Goh, Hui Hwang Zhu, Hongyu Zhang, Dongdong Wu, Thomas Guangxi Univ Coll Elect Engn Nanning 530004 Peoples R China Elect Power Res Inst Guangxi Power Grid Co Ltd Nanning 530000 Peoples R China

For the sake of increasing the energy efficiency of the city's energy supply, it is an effective approach to adopt the joint planning of the integrated energy system employing a group of cooling heat and power. However, the coupling matrix in the integrated energy system is quite difficult to formulate. In this paper, a standardized construction method for modeling Energy Hub is proposed. The construction of the model is divided into several steps. In addition, the difficult of solving the coupling matrix of integrated energy system can be availably reduced through this method. Considering the nonlinear problem caused by dispatch factors, this paper proposes a comprehensive energy system optimization strategy by using improved particle swarm optimization algorithm. Finally, using an example of a residential area with cooling, heating and electricity system to verify the effectiveness of the proposed modeling and calculation method . At the same time, the influence of demand response and energy storage on economy during operation is analyzed (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Integrated energy system Energy hub Coupling matrix particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal design of helical flute of irregular tooth end milling cutter based on particle swarm optimization algorithm

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2022年第7期236卷 3323-3339页

作者： Yu, Haibin Zheng, Minli Zhang, Wei Nie, Wanying Bian, Tianchen Harbin Univ Sci & Technol Minist Educ Coll Mech & Power Engn Key Lab Adv Mfg & Intelligent Technol Harbin 150080 Peoples R China

Due to the variable pitch angle and helix angle of the irregular tooth end milling cutter, the mass of the integral end milling cutter is eccentric, and the high stability and precision design of the irregular tooth end milling cutter is still a challenge. Aiming at the influence of dynamic balance of irregular tooth end milling cutter which can not be ignored in high-speed milling, the parameterized design of radial section of irregular tooth end milling cutter was carried out. Based on the space transformation law of the centroid of helical flute, a new method for calculating the centroid coordinate of end milling cutter was put forward, and a general mathematical model of eccentricity of integral end milling cutter was given. It was proved that this model could accurately calculate the centroid position and eccentricity of the end milling cutter. The influence of pitch difference angle and helix difference angle on eccentricity of end milling cutter was studied and analyzed. The particle swarm optimization (PSO) algorithm was creatively applied to optimize the helical flute shape of the end milling cutter, the curvature radius of helical flute curve is optimized, so that the centroid coordinate is infinitely close to the origin of coordinate. The number of iterations was set to 200. In the 32nd iteration, the result approached to infinitesimal, the final function converged, and obtained the groove curvature radius of the milling cuter with the smallest eccentricity. The optimized eccentricity of the end milling cutter is infinitesimal, which can make the vibration damping performance of the end milling cutter be fully developed. On the basis of ensuring the same cutting performance, the cutting tool unbalance was effectively reduced and the dynamic performance of milling cutter was further improved.

关键词： Keyworks End milling cutter irregular tooth helical flute mass eccentricity particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Using particle swarm optimization algorithm to search for a power ascension path of boiling water reactors

引用

ANNALS OF NUCLEAR ENERGY 2017年第Apr.期102卷 37-46页

作者： Lin, Tzung-Yi Yeh, Jau-Tyne Kuo, Weng-Sheng Inst Nucl Energy Res Nucl Engn Div 1000 Wenhua Rd Longtan Township 32546 Taoyuan County Taiwan

During the power ascension, the operating point is based on core power, core flow, control rod pattern, and concentrations of fission product, such as xenon. The thermal limits and fuel conditioning at the operating point should meet the constraints. ASCENTB is an automatic power ascension path searching program for boiling water reactors. The control rod movement is searched for by the particle swarm optimization (PSO) algorithm. The operating points of one control rod withdrawal sequence are based on the PSO1 or PSO2 strategy. The results of ASCENTS for two selected cycles are comparable with the power plant records. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： particle swarm optimization algorithm Power ascension of boiling water reactors Operating point searching strategy ASCENTB

来源：评论

学校读者我要写书评

暂无评论

Equipping Seasonal Exponential Smoothing Models with particle swarm optimization algorithm for Electricity Consumption Forecasting

引用

ENERGIES 2021年第13期14卷 4036页

作者： Deng, Changrui Zhang, Xiaoyuan Huang, Yanmei Bao, Yukun Jiangxi Univ Engn Ctr Big Data Analyt Xinyu 338029 Peoples R China Huazhong Univ Sci & Technol Sch Management Ctr Modern Informat Management Wuhan 430074 Peoples R China

Electricity consumption forecasting plays an important role in investment planning of electricity infrastructure, and in electricity production/generation and distribution. Accurate electricity consumption prediction over the mid/long term is of great interest to both practitioners and academics. Considering that monthly electricity consumption series usually show an obvious seasonal variation due to their inherent nature subject to temperature during the year, in this paper, seasonal exponential smoothing (SES) models were employed as the modeling technique, and the particle swarm optimization (PSO) algorithm was applied to find a set of near-optimal smoothing parameters. Quantitative and comprehensive assessments were performed with two real-world electricity consumption datasets on the basis of prediction accuracy and computational cost. The experimental results indicated that (1) whether the accuracy measure or the elapsed time was considered, the PSO performed better than grid search (GS) or genetic algorithm (GA);(2) the proposed PSO-based SES model with a non-trend component and additive seasonality term significantly outperformed other competitors for the majority of prediction horizons, which indicates that the model could be a promising alternative for electricity consumption forecasting.

关键词： electricity consumption forecasting seasonal exponential smoothing models particle swarm optimization algorithm grid search method genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Photon dosimetry using selective data sampling with particle swarm optimization algorithm based on NaI(Tl) scintillation detector

引用

KERNTECHNIK 2022年第3期87卷 364-372页

作者： Taheri Balanoji, Seyed Mortaza Zaki Dizaji, Hossein Abdi Saray, Akbar Imam Hossein Comprehens Univ Fac Sci Tehran Iran Urmia Univ Phys Dept Fac Sci Orumiyeh Iran

Sodium Iodide doped with Thallium NaI(Tl) scintillation detectors have potential for the development of an active dosimeter for photon radiation. We aim to show that the photon dosimetry response for NaI(Tl) scintillation detector may be optimized by employing the particle swarm optimization algorithm, when the selective data sampling is applied for the detector readout. In this work, Sodium Iodide doped with Thallium NaI(Tl) scintillation detector is considered due to being highly sensitive to gamma radiation, and one of the affordable room temperature detectors. In this research, we intend to measure the dosimetry response of the NaI(Tl) detector for various gamma sources, as an example, by measuring the ambient dose equivalent H*(10) for different gamma radioactive sources. Furthermore, we demonstrate that the photon dosimetry response may be well optimized for various energies, especially at lower energies, by increasing the energy interval number in data sampling over the NaI(Tl) scintillation detector readout with the help of an optimization algorithm. The simulation software Geant4 has been used for determining the NaI(Tl) scintillation detector readout. To this end, experimental ambient dose equivalent measurements for gamma radiation sources are compared with the theoretical results. As three and six energy intervals are considered for the selective data sampling along with an optimization algorithm based on NaI(Tl) detector output, the error percentage will be less than 20 and 10%, respectively.

关键词： ambient dose equivalent H*(10) Geant4 NaI(Tl) scintillation detector particle swarm optimization algorithm photon dosimetry response selective data sampling

来源：评论

学校读者我要写书评

暂无评论

Path Planning of Continuum Robot Based on a New Improved particle swarm optimization algorithm

引用

Journal of Harbin Institute of Technology(New Series) 2013年第4期20卷 78-84页

作者： Fang Gao Qiang Zhao Gui-Xian Li School of Mechanical Electrical Engineering Harbin Institute of Technology Traffic College Northeast Forestry University

Continuum robot is a new type of biomimetic robot,which realizes the motion by bending some parts of its *** its path planning becomes more difficult even compared with hyper-redundant *** this paper a circular arc spline interpolating method is proposed for the robot shape description,and a new two-stage position-selectable-updating particle swarm optimization(TPPSO)algorithm is put forward to solve this path planning *** algorithm decomposes the standard PSO velocity’s single-step updating formula into twostage multi-point updating,specifically adopting three points as candidates and selecting the best one as the updated position in the first half stage,and similarly taking seven points as candidates and selecting the best one as the final position in the last half *** scheme refines and widens each particle’s searching trajectory,increases the updating speed of the individual best,and improves the converging speed and *** at the optimization objective to minimize the sum of all the motion displacements of every segmental points and all the axial stretching or contracting displacements of every segment,the TPPSO algorithm is used to solve the path planning *** detailed solution procedure is *** examples of five path planning cases show that the proposed algorithm is simple,robust,and efficient.

关键词： continuum robot path planning particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

An improved particle swarm optimization algorithm for frequency-selective surface design

引用

INDIAN JOURNAL OF PHYSICS 2020年第12期94卷 1909-1915页

作者： Sheng, Xianjun Gao, Xiang Liu, Ning Dalian Univ Technol Sch Elect Engn Dalian 116024 Peoples R China

In this paper, an improved particle swarm optimization (PSO) algorithm, which can perform a global search over the search space with a faster convergence speed, is proposed for frequency-selective surface (FSS) design. Four improvement strategies including better particle initialization, acceleration coefficient dynamic adjustment, search space reset, and particle density control are applied to PSO algorithm aiming to accelerate convergence and, at the same time, improve its search capability. For verification, the improved PSO algorithm has been successfully implemented to the square loop FSS design. Then, the optimized results are compared to those obtained by the standard PSO algorithm as well as those existing in the literature, respectively, proving that the improved PSO algorithm has the capacity for accelerating convergence on the premise of ensuring the optimization accuracy.

关键词： Frequency-selective surface particle swarm optimization algorithm Equivalent circuit model 41 20 Jb 52 25 Os 02 20 -a

来源：评论

学校读者我要写书评

暂无评论

Secure and robust watermark scheme based on multiple transforms and particle swarm optimization algorithm

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2019年第2期78卷 2507-2523页

作者： Zhou, Nan Run Luo, An Wei Zou, Wei Ping Nanchang Univ Dept Elect Informat Engn Nanchang 330031 Jiangxi Peoples R China Univ Poitiers XLIM UMR CNRS 7252 Poitiers France

To improve the security, robustness and imperceptibility of watermark schemes, a novel watermark scheme is devised by fusing multiple watermark techniques, including lifting wavelet transform, discrete cosine transform, discrete fractional angular transform and singular value decomposition. To solve the false positive problem in various SVD-based watermark schemes, transform domain encryption is utilized and the embedding component of watermark instead of the whole watermark is embedded into the host image. Furthermore, the particle swarm optimization algorithm is used to optimize the scaling factors and the parameter of the improved discrete fractional angular transform. The proposed watermark scheme is tested by several attacks, such as JPEG compression, low-pass filtering, Histogram equalization, contrast enhance, and etc. Simulation results demonstrate that the proposed watermark scheme is superior in the aspects of security, robustness and imperceptibility.

关键词： Lifting wavelet transform Discrete cosine transform Discrete fractional angular transform Singular value decomposition False positive problem particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：