检索结果-内蒙古大学图书馆

Software fault prediction using Whale algorithm with genetics algorithm

SOFTWARE-PRACTICE & EXPERIENCE 2021年第5期51卷 1121-1146页

作者： Alsghaier, Hiba Akour, Mohammed Yarmouk Univ Dept Informat Syst Irbid Jordan

Software fault prediction became an essential research area in the last few years, there are many prediction and optimization techniques that have been developed for fault prediction. In this paper, an approach is developed by integrating genetics algorithm with support vector machine (SVM) classifier and Whale optimization algorithm for software fault prediction. The developed approach is applied to 24 datasets (12-NASA MDP and 12-Java open-source projects), where NASA MDP is considered as a large-scale dataset, and Java open source projects are considered as a small-scale dataset. Results indicate that integrating genetics algorithm with SVM and Whale algorithm improves the performance of the software fault prediction process when it is applied to large-scale and small-scale datasets and overcome the limitations that appeared in the previous studies.

关键词： fault prediction genetics algorithm machine learning optimization algorithms Whale algorithm

来源：评论

学校读者我要写书评

暂无评论

The recommendation of line-balancing improvement on MCM product line 1 using genetics algorithm and moodie young at XYZ Company, Co. 10

The recommendation of line-balancing improvement on MCM prod...

引用

10th International Seminar on Industrial Engineering and Management (ISIEM) - Sustainable Development in Industry and Management

作者： Sriwana, I. K. Marie, I. A. Mangala, D. Esa Unggul Univ Ind Engn Jakarta Indonesia Trisakti Univ Ind Engn Jakarta Indonesia Tarumanagara Univ Ind Engn Jakarta Indonesia

Kencana Gemilang, Co. is one electronics industry engaging in the manufacture sector. This company manufactures and assembles household electronic products, such as rice cooker, fan, iron, blender, etc. The company deals with an issue of underachievement of an established production target on MCM products line 1. This study aimed to calculate line efficiencies, delay times, and initial line smoothness indexes. The research was carried out by means of depicting a precedence diagram and gathering time data of each work element followed by examination and calculation of standard time as well as line balancing using methods of Moodie Young and Generics algorithm. Based on results of calculation, better line balancing than the existing initial conditions, i.e. improvement in the line efficiency by 18.39%, deterioration in balanced delay by 28.39%, and deterioration of a smoothness index by 23.85% was obtained.

关键词： Line Balancing Moodie Young genetics algorithm Balanced Delay

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Message Routing in Electric and Flying Vehicles Using a genetics algorithm

引用

SENSORS 2023年第3期23卷 1100-1100页

作者： Alolaiwy, Muhammad Zohdy, Mohamed Oakland Univ Elect & Comp Engn Dept Rochester MI 48309 USA

With progressive technological advancements, the time for electric vehicles (EVs) and un-manned aerial vehicles (UAVs) has finally arrived for the masses. However, intelligent transportation systems need to develop appropriate protocols that enable swift predictive communication among these battery-powered devices. In this paper, we highlight the challenges in message routing in a unified paradigm of electric and flying vehicles (EnFVs). We innovate over the existing routing scheme by considering multi-objective EnFVs message routing using a novel modified genetics algorithm. The proposed scheme identifies all possible solutions, outlines the Pareto-front, and considers the optimal solution for the best route. Moreover, the reliability, data rate, and residual energy of vehicles are considered to achieve high communication gains. An exhaustive evaluation of the proposed and three existing schemes using a New York City real geographical trace shows that the proposed scheme outperforms existing solutions and achieves a 90%+ packet delivery ratio, longer connectivity time, shortest average hop distance, and efficient energy consumption.

关键词： electric vehicles UAVs multi-objective optimization genetics algorithm EnFVs

来源：评论

学校读者我要写书评

暂无评论

Reliability Optimum Design for Bevel Gear Driven Systems Based on genetics algorithm

Reliability Optimum Design for Bevel Gear Driven Systems Bas...

引用

2016 International Conference on Artificial Intelligence and Engineering Applications (AIEA 2016)

作者： Chang Li Mingyong Hu Xing Han School of Mechanical Engineering & Automation University of Science and Technology Liaoning

ISBN: (纸本)9781510835443

genetics algorithm is a global group search optimum calculation method based on the natural selections and the genetic *** reliability design makes sure that the reliability indexes can be ***, it cannot guarantee that the products have the best working performances and the optimum design *** this paper, genetics algorithm is introduced into the reliability optimum design for bevel gear driven systems, and then the optimum design parameters of driven systems are obtained under the allowable reliability *** method can quantificational make optimum analysis for bevel gear driven systems, and is very useful for the engineering application.

关键词： Bevel gear driven systems reliability optimum design random parameters genetics algorithm

来源：评论

学校读者我要写书评

暂无评论

An efficient genetics algorithm based Z-source converter for grid connected system

引用

Research Journal of Applied Sciences, Engineering and Technology 2015年第6期10卷 630-639页

作者： Mallika, S. Saravanakumar, R. Sri Sairam Engineering College Chennai India School of Electrical Engineering VIT University Vellore India

This study deals with a simulation of robust and reliable three phase grid power interface system for photo voltaic modules using genetics algorithm based optimization technique. A control system is designed to harvest maximum solar energy under varied weather conditions with the use of a genetics algorithm based SVPWM controlled Z source fed multilevel inverter. Using Z-source networks, the system can work within a wider range of PV array output voltages than for a conventional boost converter. This study describes an modified genetics algorithm that reduces the computational burden and optimum switching angles are determined to eliminate lower order harmonics and reduces total harmonics distortion. The simulation is done using MATLAB and the simulation results are presented. © Maxwell Scientific Organization, 2015.

关键词： genetics algorithm MPPT Multilevel inverter PV array Total harmonic distortion Voltage source inverter

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Method Using Grey Wolf algorithm and Genetic algorithm for IoT Botnet DDoS Attacks Detection

引用

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2025年第1期18卷 1-61页

作者： Maazalahi, Mahdieh Hosseini, Soodeh Shahid Bahonar Univ Kerman Fac Math & Comp Dept Comp Sci Kerman Iran

The Internet of Things (IoT) is a vast network of interconnected physical objects that has improved the conditions for a computer-based physical world and improved efficiency. With the increase in communication in an IoT system, Internet security has decreased, and the most dangerous and sophisticated attacks in the IoT have emerged, i.e., DDoS and Botnet attacks. DDoS attacks are a serious threat to the availability of Internet services, especially since botnets can now be launched by almost anyone. In this situation, the use of an intrusion detection system (IDS) is essential to detect intruders and maintain the security of IoT networks. In this paper, a new IDS is proposed to detect IoT-Botnet DDoS attacks. This IDS is a new three-phase system, the first phase is related to preprocessing on the dataset and the second phase includes a new hybrid method for feature selection using filter and wrapper methods based on the Grey Wolf (GW) algorithm and genetics called GW-GA. In this method, the initial population is randomly selected and then at each stage, feature selection is done by both algorithms simultaneously and the final answer is compared and the best solutions are given as a new population to both algorithms and the third phase includes the use of machine learning and metaheuristic algorithms as classifiers. In the proposed method and to verify the performance, it is evaluated using the large BOT-IoT dataset. The results show that the proposed method significantly reduces the feature and also increases the classification accuracy compared to other methods, and the RF and Bagging algorithms have achieved a maximum recognition accuracy of 0.999. The dimensions of BOT-IoT have been reduced from 46 features to 12.

关键词： Evolutionary algorithms genetics algorithm Grey Wolf algorithm Botnet attack DDOS Meta-heuristic algorithm Machine learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Intelligent onboard assistant for maneuvering in port

引用

REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL 2016年第3期13卷 304-309页

作者： Marichal, G. N. Hernandez, A. Rojas, J. A. Melon, E. Rodriguez, J. A. Padron, I. Univ La Laguna Escuela Politecn Super Ingn Secc Nat Maquinas & Radioelect Naval C Avda Francisco Larroche S-N Santa Cruz De Tenerife 38071 Spain

An assistant onboard system is proposed in order to provide help to the captain. It is a Genetic Neuro-Fuzzy system which is able to advices about how the maneuver should be done depending on each particular situation. Particularly the casting-off is taking into account. In this way, the obstacles situated around the vessel like others boats or the port structures are considered when the maneuver is in process. Depending on the distances the system provides adequate values to the three control parameters: angle turn of tiller, principal engine power and lateral engine power.

关键词： Neuro-Fuzzy genetics algorithm vessel maneuver

来源：评论

学校读者我要写书评

暂无评论

Optimization of an agent-based model for continuous trading energy market

引用

ELECTRICAL ENGINEERING 2024年第4期106卷 4003-4017页

作者： Alberizzi, A. Di Barba, P. Mognaschi, M. E. Zani, A. Pavia Italy

The high penetration of intermittence resources in the energy market accelerates significantly the decarbonization process, but, on the other hand, the electrical system has to face the problem of unbalances. Renewable energies sources are hard to precisely forecast, and power plants are not able to predict the amount of energy that they can provide far from the real-time delivery. In this frame, the intraday market gets a fundamental role allowing agents to adjust their position close to the delivery time. In this work, we suggest an agent-based model of intraday market combined with genetics algorithms to understand what the best strategy could be adopted by players in order to optimize the market efficiency in terms of welfare and unsold quantity. In the first part, we show the effect on the market prices of different scenarios in which players aim at maximizing their revenues and selling/buying all their volumes. In the second part, we show the effect of a particular genetic algorithm on the model, focusing on how agents can adapt their strategy to enhance the market efficiency. Comparative analyses are also performed to investigate how the welfare of the system increases as well as the unsold quantity decrease when genetic algorithm is introduced.

关键词： Continuous intraday market Agent-based model genetics algorithm Power system

来源：评论

学校读者我要写书评

暂无评论

Solving partial differential equations with hybridized physic-informed neural network and optimization approach: Incorporating genetic algorithms and L-BFGS for improved accuracy

引用

ALEXANDRIA ENGINEERING JOURNAL 2023年 77卷 205-226页

作者： Pratama, Danang A. Abo-Alsabeh, Rewayda Razaq Bakar, Maharani A. Salhi, A. Ibrahim, Nur Fadhilah Univ Malaysia Terengganu Fac Ocean Engn Technol & Informat Kuala Nerus 21030 Terengganu Malaysia Univ Kufa Fac Comp Sci & Math Dept Math Kufa Iraq Univ Malaysia Terengganu Fac Ocean Engn Technol & Informat Special Interest Grp Modelling & Data Analyt Kuala Nerus 21030 Terengganu Malaysia Univ Essex Dept Math Sci Wivenhoe Pk Colchester CO43SQ Essex England

Partial differential equations (PDEs) are essential mathematical models for describing a wide range of physical phenomena. Numerically, Physic-Informed Neural Networks (PINNs), a variant of artificial neural networks, present a promising method for solving PDEs. However, due to limitation in accuracy and stability, various adaptive PINN variants have been proposed. We have designed a novel approach that adopted self-adaptive PINN (SA-PINN) with two optimization techniques: the genetic algorithm (GA) and the limited-memory Broyden-FletcherGoldfarb-Shanno (L-BFGS) algorithm. Self-adaptive PINN modifies the weights in the loss function to be fully trainable, enabling the ANN to learn and stabilize the PINN in approximating the difficult regions of the solution. GA initializes the population of ANN trainable parameters to optimize the training process with less number of iterations, while L-BFGS is used to find the best solution accurately. Our proposed approach, named SA-PINN-GA-LBFGS, is tested on solving several benchmark PDE problems including elliptic, parabolic, and hyperbolic types. We compare our results with state-of-the-art methods, demonstrating that SA-PINN-GA-LBFGS provides higher accuracy and greater efficiency. & COPY;2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria licenses/by-nc-nd/4.0/).

关键词： Self-adaptive Physics-Informed Neural Networks (SA-PINN) genetics algorithm Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) Partial Differential Equa-tions (PDEs) Optimization Techniques

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization of aniline and hydrogen production in a directly coupled membrane reactor

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2022年第19期47卷 10483-10499页

作者： Diaz, Victor Hugo Grisales Willis, Mark J. Univ Libre Secc Pereira Fac Ciencias Salud Grp Invest Microbiol & Biotecnol MICROBIOTEC Belmonte Ave Amer Pereira Colombia Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

A numerical study of aniline production by hydrogenation of nitrobenzene (NBH) and hydrogen production by steam methane reforming (SMR) in a directly coupled membrane reactor is developed. This membrane reactor was proposed aiming to decarbonize heating in SMR and to favor the recovery of all products. Aniline recovery is improved in this reactor as water, a byproduct in NBH, is consumed in SMR. The simulation is performed using a heterogeneous-one dimensional model (Dusty gas model) and results are compared against the homogeneous model. The operating conditions of the reactor were selected using a multi-objective optimization method, genetic algorithms. The aims of the optimization were: methane conversion maximization, minimum membrane area, minimum reactor size, hydrogen yield maximization, nitrobenzene conversion maximization and the maximization of hydrogen recovery. This process was able to achieve complete conversion of methane and nitrobenzene. The hydrogen yield achieved can be as high as the maximum (similar to 4). 35% of this hydrogen was used as a reactant for aniline production. 99% of the unreacted hydrogen was recovered and purified. As the steam flow was minimized, aniline was obtained with a molar composition (70%), 2.1 times higher than that obtained in a conventional process for aniline production (33%). CO2 was obtained with a purity of 97%, hence, CO2 carbon capture and storage techniques were also favored. In addition, the energy requirements of heating of feedstock, reaction and recovery system of this novel process was 2.7 times lower than that of conventional processes carried out independently. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Multi-objective optimization Nitrobenzene hydrogenation Steam methane reformer genetics algorithm Autothermal membrane reactor

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：