检索结果-内蒙古大学图书馆

IOT Energy Consumption Based on pso-shortest Path Techniques

RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2020年第7期13卷 993-1000页

作者： Wadday, Ahmed G. Al-hchaimi, Ahmed A. J. Ibrahim, Ahmed J. Al Furat Al Awsat Tech Univ Engn Tech Coll Al Najaf Iraq Southern Tech Univ Thi Qar Tech Coll Thi Qar Iraq

Background: The Internet of Thing is a network that enables multiple hardware devices, sensors and other home applications from electronically communicate with each other. New era such technology is increasing importance mainly due to the revolutionary development of information technologies. Methods: However, energy efficiency is still a big challenge facing IoT technology. Thus, it becomes an interesting topic for many researchers to investigate. Current work aims to reduce the energy consumption thereby introducing the shortest path technique and another new practicing for Particle Swarm Optimization algorithm in the Internet of Thing cooperative clusters. Results: The main concept is based on cluster heads cooperation with each other known as Cooperative Clusters to transfer information to the base station. The Primary results reveals a 17% and 16% reduction in energy consumption was achieved over the shortest path technique and Particle Swarm Optimization algorithm respectively. Results also show a remarkable improvement in the system lifetime due to the new applied scheme. Conclusion: The other method is by pso algothrim at beginig it sending Randomly then it will select the path by using the feed back acknowledgment after that it will collect the information by sending it for the Cluster heads by updating the information status automatically. That's why we discovered the pso advantages than the others.

关键词： Cooperative clusters IOT pso energy consumption cooperative clusters pso algorithm

来源：评论

学校读者我要写书评

暂无评论

Coupled NEGF-pso method for maximizing the current ratio of CNTFETs based on oxide thickness optimization

引用

JOURNAL OF COMPUTATIONAL ELECTRONICS 2021年第5期20卷 1657-1665页

作者： Ghasemi Nejad Raeini, Amin Kordrostami, Zoheir Hamedi, Samaneh Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

A method for designing carbon nanotube field-effect transistors (CNTFETs) with optimized oxide thickness is proposed herein. The optimum oxide thickness that provides the maximum current ratio (on/off ratio) is calculated for each design. The effect of oxide thickness on the on/off ratio is investigated by treating it as the independent variable and calculating the on-state and off-state currents. Particle swarm optimization is used to determine the exact optimum oxide thickness to achieve the maximum current ratio, which is one of the most important parameters in switching applications. The optimum insulator thickness is calculated for CNTFETs with different chiral vectors, insulator types, channel lengths and source/drain doping levels. For further study of the CNTFETs, performance parameters including cutoff frequency and transconductance of the devices are also calculated and investigated. The results show that CNTFET designers should select the oxide thickness very carefully, not simply based on reported values in other works. Each design requires its own optimum oxide thickness which provides the maximum on/off current ratio only for that design.

关键词： Optimization CNTFET Current ratio Oxide thickness pso algorithm

来源：评论

学校读者我要写书评

暂无评论

A three-stage pso-based methodology for tuning an optimal PD-controller for robotic arm manipulators

引用

EVOLUTIONARY INTELLIGENCE 2022年第1期15卷 381-396页

作者： Tutunji, Tarek A. Al-Khawaldeh, Mustafa Alkayyali, Malek Philadelphia Univ Mechatron Engn Dept Amman Jordan Clemson Univ Dept Mech Engn Clemson SC USA

Six degrees-of-freedom (DoF) robot manipulators are dynamically coupled and highly nonlinear multi-variable systems. Calculating the optimal joint angles from the operational space (i.e. inverse kinematics) and designing the optimal joint controller parameters are two important research topics. This paper proposes a 3-stage Particle Swarm Optimization (pso)-based methodology for solving the inverse kinematics and optimizing the controller parameters. In the first stage, a pso algorithm solves the inverse kinematics problem by minimizing a multi-objective cost function in the operational space (i.e. the error in the end-effector's pose) and therefore finds the optimal joint angles. In the second stage, polynomial functions generate the desired trajectory between the initial and final poses in the joint space. Finally, a second pso algorithm tunes six proportional-derivative (PD) controllers, one for each joint, to track the desired trajectory by minimizing another multi-objective cost function in the joint space. Two case studies, based on six DoF Puma 560, validate the performance of the proposed methodology. Simulation results show that the proposed 3-stage methodology provides fast and accurate results as the pso algorithms are effective in solving the inverse kinematics problem and tuning the optimal PD parameters.

关键词： Robot manipulator Nonlinear dynamics Optimization pso algorithm Inverse kinematics Trajectory tracking PD-control PUMA 560

来源：评论

学校读者我要写书评

暂无评论

Using pso and ABC Routing algorithms Reducing Consumed Energy in Underwater Wireless Sensor Networks

引用

IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING 2022年第2期46卷 367-380页

作者： Kharati, Ehsan Islamic Azad Univ Dept Comp Engn Arak Branch Arak Iran

The main challenge in Underwater Wireless Sensor Networks (UWSN) is reducing consumed energy and while extending the lifetime of the network. Mobile Sinks (MSs) and optimum data transmission routing between Sensor Nodes (SNs) are widely employed to overcome this problem. Particle Swarm Optimization (pso) is one of the heuristic algorithms for optimizing data routing, but it has some drawbacks, including the risk of early convergence, inaccurate solution presentation, and local minimal. One of the reasons for this issue is a lack of thorough searching and checking of the search space. To tackle this problem, in this paper we propose a routing algorithm based on pso and Artificial Bee Colony (ABC) algorithms to investigate the search space more accurately, lower the chance of falling in local minimal, and prevent wrong solution and early convergence. However, combining the two pso and ABC algorithms slows the suggested algorithm, which can be solved by executing parallel loops. Simulation results show that increasing the number of iterations and SNs improve the routing performance in the proposed algorithm better than the pso, Genetic algorithm, and Clustering algorithms. In addition, the network lifetime will be increased by about 5 to 10%, consumed energy will be decreased by about 5 to 20%, and except for the start period, the number of disabled SNs will be reduced by 20 to 30%;nevertheless, the run time will be increased.

关键词： pso algorithm ABC algorithm Underwater Wireless Sensor Networks Data Routing

来源：评论

学校读者我要写书评

暂无评论

Improved State Space Model Using Iterative pso for Unsteady Aerodynamic System at High AOA

引用

INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2018年第3期12卷 1-17页

作者： Luo, Guiming Zhao, Boxu Jiang, Mengqi Tsinghua Univ Sch Software Beijing Peoples R China

Due to the complex hysteresis phenomenon at a high angle of attack (AOA), modeling of unsteady aerodynamic coefficients usually encounters the problem that the parameter vector is too long and the simulation accuracy is not high. The article proposes an improved state-space model based on aerodynamics, applying Fourier analysis and the principal component analysis for model optimization. The likelihood criterion and GOIpso (Iterative Particle Swarm Optimization Based on Genetic Operator) algorithm are established under the Gaussian assumption. The iterative pso, into which the genetic algorithm's operators are integrated to calculate the optimization of the likelihood function, greatly reduced the probability of local optimization. Experiments show that the algorithm and model proposed in this paper greatly improves the model-fitting accuracy.

关键词： High Angle of Attack pso algorithm State Space Model Unsteady Aerodynamic System

来源：评论

学校读者我要写书评

暂无评论

A pso-GRNN model for railway freight volume prediction: Empirical study from China

引用

JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT-JIEM 2014年第2期7卷 413-433页

作者： Sun, Yan Lang, Maoxiang Wang, Danzhu Liu, Linyun Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China Northeastern Univ Coll Engn Boston MA 02115 USA

Purpose: In this study, we aim to design a mathematical model for railway freight volume prediction which can provide an accurate direction for railway freight resource allocation. Based on the precise prediction, railway freight enterprises are able to optimize and integrate the limited resources to organize freight transport more efficiently and economically. Design/methodology/approach: In this study, we design a pso-GRNN model to predict railway freight volume. In the proposed model, GRNN carries out the nonlinear regression analysis between railway freight volume and its influencing factors which can be described by detailed and measurable indexes and outputs the prediction value. pso algorithm with time linear decreasing inertia weight and time varying acceleration coefficients is applied to optimize the basic GRNN model by searching the optimal smoothing parameter. Findings: The simulation result in this study indicates that (1) the pso-GRNN model is able to predict railway freight volume by using the value of other relevant indexes as its input to fit the variation of railway freight volume;(2) Through optimization for GRNN model based on pso algorithm, the proposed model performs well prediction accuracy;(3) Compared with RBFNN model and BPNN model, the superiority of the proposed model in prediction accuracy and curve fitting capacity is verified. Originality/value: In the empirical study from China, we establish a railway freight volume prediction index system containing seventeen prediction indexes from five influencing factors. Then we construct the pso-GRNN model to predict the railway freight volume from 2007 to 2011 by using data from 1990 to 2006 as training samples. In order to verify the feasibility and prediction accuracy of the proposed model, we also use two widely applied neural network models, including RBFNN model and BPNN model, to estimate the railway freight volume prediction during the same period. Compared with RBFNN model and BPNN mode

关键词： railway freight volume prediction model neural network GRNN smoothing parameter pso algorithm

来源：评论

学校读者我要写书评

暂无评论

pso-Markov residual correction method based on Verhulst-Fourier prediction model

引用

SYSTEMS SCIENCE & CONTROL ENGINEERING 2021年第1期9卷 32-43页

作者： Niu, Tong Zhang, Lin Zhang, Bo Li, Bo Zhang, Baoshan Wang, Wenfeng Air Force Engn Grad Sch Xian Peoples R China Air Force Engn Air & Missile Def Coll Xian Peoples R China

Macroeconomic predicting is a research hotspot in the field of predicting. The accuracy of predicting often directly affects the rationality of decision-making, especially for defense expenditure predicting. This paper studies the residual correction method of prediction model based on time series. Firstly, based on the grey nonlinear Verhulst prediction model, Fourier series is introduced in this paper to correct the residual sequence once and establish a residual correction model. On this basis, this paper also introduces Markov related concepts, creatively introduces the two-dimensional residual data into Markov state transition matrix, classifies it by K-means clustering analysis, and calculates its parameters by pso algorithm to realize the secondary accurate correction of residual. Finally, a pso-Markov residual correction method based on Verhulst-Fourier model is proposed. Tested by examples, this method effectively improves the prediction accuracy of the model, and the prediction is more reliable and accurate.

关键词： Residual correction national defense expenditure prediction Verhulst-Fourier model Markov model pso algorithm

来源：评论

学校读者我要写书评

暂无评论

pso type-reduction method for geometric interval type-2 fuzzy logic systems

引用

Journal of Harbin Institute of Technology(New Series) 2008年第6期15卷 862-867页

作者：赵先章高一波曾隽芳杨一平 Institute of Automation Chinese Academy of Sciences China Agricultural University

In a special case of type-2 fuzzy logic systems （FLS）, i.e. geometric inteIval type-2 fuzzy logic systems （GIT-2FLS）, the crisp output is obtained by computing the geometric center of footprint of uncertainly （FOU） without type-reduction, but the defuzzifying method acts against the corner concepts of type-2 fuzzy sets in some cases. In this paper, a pso type-reduction method for GIT-2FLS based on the particle swarm optimization （pso） algorithm is presented. With the pso type-reduction, the inference principle of geometric interval FLS operating on the continuous domain is consistent with that of traditional interval type-2 FLS operating on the discrete domain. With comparative experiments, it is proved that the pso type-reduction exhibits good performance, and is a satisfactory complement for the theory of GIT-2FLS.

关键词： interval type-2 fuzzy sets pso algorithm type-reduction

来源：评论

学校读者我要写书评

暂无评论

Coordinated Robust Control Scheme for Rotor angle and Voltage Oscillations Damping via STATCOM based on pso 28

Coordinated Robust Control Scheme for Rotor angle and Voltag...

引用

28th Iranian Conference on Electrical Engineering (ICEE)

作者： Kashani, Mahsa Alfi, Alireza Shahrood Univ Technol Fac Elect & Robot Engn Shahrood Iran

ISBN: (纸本)9781728172965

STATCOM is a controllable reactive current source applied to control reactive flow in transmission lines and compensate reactive power in power system nodes. This paper gives a novel robust control scheme for designing STATCOM controller to enhance the stability of the power gird. In order to mitigate oscillations, the coordinated controller is carried out both speed and voltage control loop. The proposed scheme is defined as an optimization problem, and the robustness criteria are used for evaluating the controller stability and performance. Also, Single Machin Infinite Bus (SMIB) system are applied to analyze the dynamic stability. The employed controller is a PID controller and its coefficients are tuned by pso algorithm. The simulation results show that the proposed controller extremely obtains significant damping characteristics during the operation process.

关键词： Power system stability STATCOM PID controller pso algorithm

来源：评论

学校读者我要写书评

暂无评论

A Multi-swarm pso and its Application in Operational Optimization of Ethylene Cracking Furnace

A Multi-swarm PSO and its Application in Operational Optimiz...

引用

7th World Congress on Intelligent Control and Automation

作者： Geng, Zhiqiang Zhu, Qunxiong Beijing Univ Chem Technol Coll Informat Sci &Technol Beijing 100029 Peoples R China

ISBN: (纸本)9781424421138

The exiting pso algorithms are analyzed deeply, a multi-swarm pso (MSpso) is studied. The whole swarm is divided into three sub-swarms randomly, the first particle group obeys the standard pso principle to search the optimal result, the second searches randomly inner neighborhood of the optimal result, the third does not care about the optimal result but flies freely according to themselves velocities and positions. So the algorithm enhances its global searching space, enriches particles' diversity in order to let particles jump out local optimization points. Testing and comparing results with standard pso and linearly decreasing weight pso by several widely used benchmark functions show optimization performance of the algorithm is better. Furthermore, the proposed algorithm is employed to resolve the operational optimization problems of ethylene cracking furnace. The operational optimization results for built cracking model are effective and satisfying.

关键词： pso algorithm Ethylene cracking furnace Operational optimization

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：