检索结果-内蒙古大学图书馆

A grasshopper optimization algorithm-Based Response Surface Method for Non-Probabilistic Structural Reliability Analysis with an Implicit Performance Function

引用

BUILDINGS 2022年第7期12卷 1061页

作者： Li, Qi Wang, Junmu Su, Guoshao Guangxi Polytech Construct Sch Civil Engn Nanning 530007 Peoples R China Guangxi Univ Coll Civil Engn & Architecture Key Lab Disaster Prevent & Struct Safety Minist Educ Nanning 530004 Peoples R China Guangxi Univ Guangxi Prov Engn Res Ctr Water Secur & Intellige Nanning 530004 Peoples R China

Non-probabilistic reliability analysis has great developmental potential in the field of structural reliability analysis, as it is often difficult to obtain enough samples to construct an accurate probability distribution function of random variables based on probabilistic theory. In practical engineering cases, the performance function (PF) is commonly implicit. Monte Carlo simulation (MCS) is commonly used for structural reliability analysis with implicit PFs. However, MCS requires the calculation of thousands of PF values. Such calculation could be time-consuming when the structural systems are complicated, and numerical analysis procedures such as the finite element method have to be adopted to obtain the PF values. To address this issue, this paper presents a grasshopper optimization algorithm-based response surface method (RSM). First, the method employs a quadratic polynomial to approximate the implicit PF with a small set of the actual values of the implicit PF. Second, the grasshopper optimization algorithm (GOA) is used to search for the global optimal solution of the scaling factor of the convex set since the problem of solving the reliability index is transformed into an unconstrained optimal problem. During the search process in the GOA, a dynamic response surface updating strategy is used to improve the approximate accuracy near the current optimal point to improve the computing efficiency. Two mathematical examples and two engineering structure examples that use the proposed method are given to verify its feasibility. The results compare favorably with those of MCS. The proposed method can be non-invasively combined with finite element analysis software to solve non-probabilistic reliability analysis problems of structures with implicit PF with high efficiency and high accuracy.

关键词： non-probabilistic reliability analysis response surface method grasshopper optimization algorithm finite element analysis

来源：评论

学校读者我要写书评

暂无评论

An automation query expansion strategy for information retrieval by using fuzzy based grasshopper optimization algorithm on medical datasets

引用

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2023年第3期35卷 e7418-e7418页

作者： Srivel, R. Kalaiselvi, K. Shanthi, S. Perumal, Uma Adhiparasakthi Engn Coll Dept CSE Melmaruvathur Tamil Nadu India SRM Inst Sci & Technol Dept Networking & Commun Chennai India Malla Reddy Coll Engn & Technol Dept CSE Hyderabad India Jazan Univ Jazan Saudi Arabia

Due to the technical words employed, which are primarily recognized by medical specialists, information retrieval in the medical area is sometimes described as sophisticated. Because of this, users frequently have trouble coming up with queries utilizing these medical phrases. However, this problem may be readily fixed by an information retrieval system that finds the pertinent terms that fit the user's query and automatically creates a ranking document using these keywords. To enhance the IR performance, the Automatic Query expansion method is applied by appending additional query terms for the medical domain. We propose a novel fuzzy-based grasshopper optimization algorithm (GOA) based on automatic query expansion. This work is mainly focused on filtering the most relevant augmented query by utilizing the synchronization score of IR evidence like normalized term frequency, inverse document frequency, and normalization of document length. The main aim of this work is to identify the medical terms that appropriately match the user's queries. The GOA algorithm ranks the terms based on relevance and then identifies the terms with the maximum synchronization value. The documents formed using the optimal expanded query are classified into three types, namely totally relevant, moderately relevant, and marginally relevant. Besides, the comparison of the proposed work is carried out for different performance metrics like Mean-Average Precision, F-measure, Precision-recall, and Precision rank are evaluated and analyzed by using TREC-COVID, TREC Genomics 2007, and MEDLARs medical datasets for the proposed and some of the state-of-art works. For a total of 60 queries, the proposed model offers an F1-Score of 0.964, 0.959, and 0.968 for the MEDLARS, TREC Genomics, and TREC COVID19 datasets, respectively. The E1-score and Mean Reciprocal Rate (MRR) of the proposed model is 0.8 and 0.9 when evaluated using the TREC COVID19 dataset. Performance analyses show that the proposed app

关键词： accelerated particle swarm optimization COVID fuzzy logic grasshopper optimization algorithm query expansion

来源：评论

学校读者我要写书评

暂无评论

Hybridizing Teaching-Learning-Based optimization With Adaptive grasshopper optimization algorithm for Abrupt Motion Tracking

引用

IEEE ACCESS 2019年 7卷 168575-168592页

作者： Zhang, Huanlong Gao, Zeng Ma, Xiaoyang Zhang, Jie Zhang, Jianwei Zhengzhou Univ Light Ind Coll Elect & Informat Engn Zhengzhou 450002 Peoples R China Zhengzhou Univ Light Ind Software Engn Coll Zhengzhou 450002 Peoples R China

Aiming at the problem that conventional tracking algorithms are difficult to deal with abrupt motion efficiently, an optimization algorithm called hybrid Teaching-learning-based optimization with Adaptive grasshopper optimization algorithm (TLGOA) is proposed in this paper. Firstly, the non-linear strategy based on tangent function is used to replace the linear mechanism in the standard grasshopper optimization algorithm (GOA). The improved adaptive GOA (AGOA) can avoid the local trapping problem and enhance the global optimization ability, which can handle the problem of abrupt motion. Secondly, considering that Teaching-learning-based optimization (TLBO) has obviously local exploitation operator and fast convergence, a hybrid TLGOA tracker is designed by combining the advantages of both AGOA and TLBO. The approach can enable better tracking accuracy and efficiency. Finally, extensive experimental results show that the proposed algorithm has obvious advantages over other algorithms, and also prove that TLGOA tracker is very competitive compared to other state-of-the-art trackers, especially for abrupt motion tracking.

关键词： Visual tracking abrupt motion grasshopper optimization algorithm teaching-learning-based optimization

来源：评论

学校读者我要写书评

暂无评论

Improved grasshopper optimization algorithm to solve energy consuming reduction of chiller loading

引用

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2024年第1期46卷 2511-2524页

作者： Xu Wenhan Wan Yuanxing Di Qi Rouyendegh, Babak Daneshvar Nanjing Audit Univ Sch Accounting Nanjing Jiangsu Peoples R China Zhejiang Gongshang Univ Sch Accounting Hangzhou Zhejiang Peoples R China Univ Int Business & Econ Business Sch Beijing Peoples R China Ankara Yildirim Beyazit Univ Dept Ind Engn Ankara Turkiye

This paper presents a new improved version of grasshopper optimization algorithm (GOA) to find the optimal solution for the optimal chiller loading (OCL) problem subject to obtain the minimum power consumption. To improve the convergence speed of the GOA algorithm, chaos theory is employed. To validate the proposed method, it is compared with three different OCL case studies and the results are compared with GA, WCO, PSO, and original GOA to demonstrate the capability of the presented system. Simulation results showed that the presented chaos GOA gives better (or equal) results compared with other studied methods.

关键词： Optimal chiller loading grasshopper optimization algorithm chaos theory energy consumption

来源：评论

学校读者我要写书评

暂无评论

Automatic generation controller for multi area multisource regulated power system using grasshopper optimization algorithm with fuzzy predictivePIDcontroller

引用

INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2021年第1期34卷

作者： Kumar, Rajiv Sharma, V. K. Bhagwant Univ Dept Elect Engn Ajmer 305004 Rajasthan India

This paper presents a fuzzy predictive-proportional integral derivative (FP-PID) controller approach for automatic generation controller (AGC). This new AGC approach aims to balance the total generating system without any power losses and load changes in keeping constant system frequency per tie-lie power flow. But, a sudden load variation in multi-area Interconnected power system (MIPS) creates nonlinearities (frequency deviation & tie-line) in all control areas. Because, penetrating of renewable sources to the power system, the sluggish control action may cause inefficiency in migrating frequency and tie-line power flow. Hence, an accurate and fast-acting controller is required to maintain the nominal value also the quality and stability of power system, because traditional AGC is not feasible for further process. Here, we propose an FP-PID controller in MIPS for controlling large parametric uncertainties. Modeling error is taken into account to reduce the maximum deviation and time of oscillation. The main purpose of FP-PID based AGC is to ensure stable and reliable power system operation. A grasshopper optimization algorithm (GOA) is used to tune the parameters of FP-PID controller with Integral of time multiplied squared error (ITSE) as the objective function. The proposed method is compared with conventional two-area and three-area system, the result are built-in Simulink/MATLAB show that the proposed method has a good dynamic response, fast operation reduced magnitude error and minimized frequency transients for three power areas. The robustness of the controller is, it need not be retuned for wide variations in system parameters and random step load power.

关键词： automatic generation control Fuzzy predictive PID grasshopper optimization algorithm Multi-area interconnected power system

来源：评论

学校读者我要写书评

暂无评论

Hybrid grasshopper optimization algorithm and Differential Evolution for Multilevel Satellite Image Segmentation

引用

REMOTE SENSING 2019年第9期11卷 1134-1134页

作者： Jia, Heming Lang, Chunbo Oliva, Diego Song, Wenlong Peng, Xiaoxu Northeast Forestry Univ Coll Mech & Elect Engn Harbin 150040 Heilongjiang Peoples R China Univ Guadalajara Dept Ciencias Computac CUCEI Ave Revoluc 1500 Guadalajara 44430 Jalisco Mexico

An efficient satellite image segmentation method based on a hybrid grasshopper optimization algorithm (GOA) and minimum cross entropy (MCE) is proposed in this paper. The proposal is known as GOA-jDE, and it merges GOA with self-adaptive differential evolution (jDE) to improve the search efficiency, preserving the population diversity especially in the later iterations. A series of experiments is conducted on various satellite images for evaluating the performance of the algorithm. Both low and high levels of the segmentation are taken into account, increasing the dimensionality of the problem. The proposed approach is compared with the standard color image thresholding methods, as well as the advanced satellite image thresholding techniques based on different criteria. Friedman test and Wilcoxon's rank sum test are performed to assess the significant difference between the algorithms. The superiority of the proposed method is illustrated from different aspects, such as average fitness function value, peak signal to noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), standard deviation (STD), convergence performance, and computation time. Furthermore, natural images from the Berkeley segmentation dataset are also used to validate the strong robustness of the proposed method.

关键词： satellite image image segmentation image thresholding hybrid optimization grasshopper optimization algorithm differential evolution minimum cross entropy

来源：评论

学校读者我要写书评

暂无评论

Non-linear Channel Equalization using Modified grasshopper optimization algorithm

引用

APPLIED SOFT COMPUTING 2024年 153卷

作者： Ingle, Kishor Kisan Jatoth, Ravi Kumar Natl Inst Technol Warangal Dept Elect & Commun Engn Warangal 506004 Telangana India

In this paper, a modified grasshopper optimization algorithm is proposed for equalization of non-linear wireless communication channels. Even though grasshopper optimisation algorithm (GOA) is an efficient algorithm, it gets trapped into local optima after some iterations due to loss of swarm diversity. Furthermore, GOA does not involve any provision to retain the elite grasshoppers found so far at each index which weakens the exploitation capability and convergence rate of GOA. These limitations of GOA are alleviated in this paper by incorporating three key modifications into GOA. A threshold parameter is introduced to detect the inefficient search region. Le ' vy Flight is integrated with the basic GOA to improve the diversity of grasshopper swarm and the greedy selection operator is used to preserve the elite grasshoppers found so far at every index. The superiority of a modified grasshopper optimization algorithm (MGOA) is illustrated over the existing metaheuristic algorithms. The key parameters of MGOA are selected by performing the sensitivity analysis. The simulation results on four non-linear channels demonstrate the equalization capability of the proposed MGOA in terms of MSE and BER performance. A statistical validity of results provided by MGOA is confirmed through Wilcoxon rank -sum test.

关键词： Channel equalization Metaheuristic algorithms grasshopper optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal Reactive Power Dispatch and Demand Response in Electricity Market Using Multi-Objective grasshopper optimization algorithm

引用

PROCESSES 2024年第9期12卷 2049页

作者： Das, Punam Dawn, Subhojit Gope, Sadhan Das, Diptanu Salata, Ferdinando Natl Inst Technol Agartala NITA Dept Elect Engn Agartala 799046 India Velagapudi Ramakrishna Siddhartha Engn Coll Dept Elect & Elect Engn Vijayawada 520007 India Sapienza Univ Rome Fac Civil & Ind Engn DIAEE I-00185 Rome Italy

Optimal Reactive Power Dispatch (ORPD) is a power system optimization tool that modifies system control variables such as bus voltage and transformer tap settings, and it compensates devices' Volt Ampere Reactive (VAR) output. It is used to decrease real power loss, enhance the voltage profile, and promote stability. Furthermore, several issues have been faced in electricity markets, such as price volatility, transmission line congestion, and an increase in the cost of electricity during peak hours. Programs such as demand response (DR) provide system operators with more control over how small customers participate in lowering peak-hour energy prices and demand. This paper presents an extensive study on ORPD methodologies and DR programs for lowering voltage deviation, limiting cost, and minimizing power losses to create effective and economical operations systems. The main objectives of this work are to minimize costs and losses in the system and reduce voltage variation. The grasshopper optimization algorithm (GOA) and Dragonfly algorithm (DA) have been implemented successfully to solve this problem. The proposed technique has been evaluated by using the IEEE-30 bus system. The results obtained by the implementation of demand response systems show a considerable reduction in costs and load demands that benefit consumers through DR considerations. The results obtained from the GOA and DA are compared with those generated by other researchers and published in the literature to ascertain the algorithm's efficiency.

关键词： demand response electricity markets grasshopper optimization algorithm Optimal Reactive Power Dispatch

来源：评论

学校读者我要写书评

暂无评论

Optimal load shedding scheme using grasshopper optimization algorithm for islanded power system with distributed energy resources

引用

AIN SHAMS ENGINEERING JOURNAL 2023年第1期14卷

作者： Ahmadipour, Masoud Othman, Muhammad Murtadha Salam, Zainal Alrifaey, Moath Ridha, Hussein Mohammed Veerasamy, Veerapandiyan Univ Teknol MARA Coll Engn Sch Elect Engn Shah Alam 40450 Selangor Malaysia Univ Teknol Malaysia Ctr Elect Energy Syst Sch Elect Engn Johor Baharu 81310 Malaysia Univ Putra Malaysia Fac Engn Dept Mech & Mfg Engn Serdang 43400 Selangor Malaysia Univ Putra Malaysia Fac Engn Adv Lightning Power & Energy Res ALPER Serdang Selangor Malaysia Nanyang Technol Univ NTU Sch Elect & Elect Engn Singapore Singapore

In this paper, a new optimal load shedding method using a grasshopper optimization algorithm (GOA) is proposed for maintaining the stability of the islanded power system that comprises distributed energy resources (DER). The GOA is used in conjunction with the method of voltage stability margin (VSM) to handle the multi-objective shedding constraints, namely the generation restrictions, allowable load cur-tailment, and load priority. To assess the effectiveness of the offered method, a comprehensive evaluation study is applied to a system of IEEE 33-bus and four DG units in view of different scenarios. Furthermore, the effectiveness of performance of the GOA-based load shedding is compared in terms of fitness value, voltage stability margin, and percentage of load that should be curtailed with three well-known opti-mization approaches (i.e., the particle swarm optimization (PSO), grey wolf optimization (GW), and genetic algorithm (GA)) under different islanded scenarios. The obtained results show that the perfor-mance of the proposed method is better than other methods with the less value of load curtailed for totally islanded states (i.e., 45.67% for island A, 16.63% for island B, 38.05% for island C, and 27.98% for island D in this study). In addition, the results of the simulation display the efficacy of the proposed scheme to ensure voltage stability with the optimal load quantity to be shed for dissimilar islanding scenarios.& COPY;2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams Uni-versity. This is an open access article under the CC BY-NC-ND license (http://***/licenses/ by-nc-nd/4.0/).

关键词： Optimal load shedding Islanded power system Voltage collapse Voltage stability margin grasshopper optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

引用

EXPERT SYSTEMS 2021年第3期38卷 e12666-e12666页

作者： Yildiz, Betul Sultan Pholdee, Nantiwat Bureerat, Sujin Yildiz, Ali Riza Sait, Sadiq M. Bursa Uludag Univ Dept Elect & Energy TR-16059 Gorukle Turkey Khon Kaen Univ Fac Engn Sustainable Infrastruct Res & Dev Ctr Dept Mech Engn Khon Kaen Thailand Bursa Uludag Univ Dept Automot Engn Gorukle Turkey King Fahd Univ Petr & Minerals Dept Comp Engn Dhahran Saudi Arabia

Structural design and optimization are important topics for the control and design of industrial robots. The motivation behind this research is to design a robot gripper mechanism. To explore robust design of the robot gripper mechanism, a new optimization approach based on a grasshopper optimization algorithm and Nelder-Mead algorithm is developed for requiring a fast and accurate solution. Additionally, a vehicle side crash design problem, a multi-clutch disc problem, and a manufacturing optimization problem are solved with the developed method to show the advantages of the new technique (HGOANM). Both engineering comparisons and production problem results in which HGOANM is applied are compared with the latest optimization techniques in the literature. The results of the problems resolved in this article reveal that the developed HGOANM is an essential optimization approach by solving real-world engineering problems quickly and accurately.

关键词： grasshopper optimization algorithm hybrid algorithm multi‐ clutch disc Nelder Mead robot gripper mechanism robust design vehicle crash

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：