检索结果-内蒙古大学图书馆

OPTIMIZATION-DRIVEN DEEP RECURRENT NEURAL NETWORK FOR INTRUSION DETECTION AND HEALTH RISK ASSESSMENT IN WIRELESS BODY SENSOR NETWORK

引用

BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS 2021年第1期33卷

作者： Alameen, Abdalla Gupta, Ashu Prince Sattam Bin Abdulaziz Univ Coll Arts & Sci Dept Comp Sci Wadi Al Dawasir Saudi Arabia

Wireless body sensor network (WBSN) has gained great attention in the environmental and military applications, but security is the major issue, nowadays. In addition, the data exchanged through the wireless sensor network (WSN) is vulnerable to several malicious attacks because of the physical defense equipment needs. Hence, various intrusion detection methods are required for defending against such attacks. Accordingly, an effective method, named deep recurrent neural network (Deep RNN), is proposed in this research for detecting the intrusion in WBSN. At first, the WBSN nodes are utilized to sense the data from the health records of patient for acquiring certain parameters to make risk assessment. Then, WBSN nodes transmit the data to the target nodes using the obtained parameters. After the determination of parameters, the WBSN nodes are responsible to collect the information of the patient and transfer the obtained information to cluster heads (CHs) based on the hybrid harmony search algorithm-particle swarm optimization (HSA-PSO). HSA-PSO is utilized for identifying the optimal CH node iteratively. From the selected CHs, secure communication is done to exchange the data packets. After that, the KDD features are extracted and intrusion detection is done using the proposed Deep RNN. After the genuine users are detected, the classification is done using fractional cat-based salp swarm algorithm (FCSSA) for the risk assessment. The performance of the intrusion detection and health risk assessment in WBSN based on the proposed model is evaluated based on accuracy, sensitivity, and the specificity. The developed model achieves the maximal accuracy of 95.79%, maximal sensitivity of 95.97%, and the maximal specificity of 95.61% using Cleveland dataset.

关键词： Wireless body sensor network Deep recurrent neural network harmony search algorithm Salp swarm algorithm Particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Study on HS-RNN in Vibration Prediction of Mechanical Spindle

Study on HS-RNN in Vibration Prediction of Mechanical Spindl...

引用

第33届中国控制与决策会议

作者： Jinxiang Pian Masuma Rifah Tamanna Alkasim Usman ABDULMAJID Academy School of Information and Control Engineering Shenyang Jianzhu University International school Shenyang Jianzhu University

Mechanical spindle in the high-speed operation due to an uneven distribution of the rotor mass,causing the spindle to vibrate thus affecting its ***,the model of mechanical spindle vibration prediction is of great *** mechanism of mechanical spindle vibration prediction is complex,and the amplitude of vibration varies nonlinearly with the *** is difficult to establish accurate model of mechanical spindle vibration *** this paper,RNN(Recurrent Neural Network) recurrent neural network is used to establish the model of mechanical spindle vibration *** vibration amplitude of the built-in balance block at different positions and spindle speeds is *** search(HS)Through self-learning update,thereby improving the accuracy of the mechanical spindle vibration prediction *** experimental results show that the HS-RNN-based mechanical spindle vibration prediction method proposed in this paper can automatically determine the network structure and accurately predict the vibration amplitude of the mechanical spindle.

关键词： harmony search algorithm RNN Recurrent Neural Network Vibration Prediction Mechanical Spindle

来源：评论

学校读者我要写书评

暂无评论

A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks

引用

ANNALS OF TELECOMMUNICATIONS 2018年第5-6期73卷 353-365页

作者： Alia, Osama Moh'd Univ Tabuk Fac Comp & Informat Technol Dept Comp Sci POB 741 Tabuk 71491 Saudi Arabia

In the development of cluster-based energy-efficient protocols for wireless sensor networks (WSNs), a particularly challenging problem is the dynamic organization of sensors into a wireless communication network and the routing of sensed information from the field sensors to a remote base station (BS) in a manner that prolongs the lifetime of WSNs. This paper presents a new energy-efficient clustering protocol for WSNs, which can minimize total network energy dissipation while maximizing network lifetime. The protocol is divided into two parts. The first deals with constructing an infrastructure for the given WSN. A newly developed algorithm, based on a harmony search (HS), automatically determines the optimal number of clusters and allocates sensors into these clusters. This algorithm also eliminates the need to set the number of clusters a priori. The second part is concerned with the process of sending sensed data from nodes to their cluster head and then to the BS. A decentralized fuzzy clustering algorithm is proposed, where the selection of cluster heads in each round is locally made in each cluster during the network lifetime. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, prolong the network lifetime and increase the data delivery at the BS, when compared to other well-known clustering-based routing protocols.

关键词： Wireless sensor networks Energy-efficient routing protocols harmony search algorithm Fuzzy clustering

来源：评论

学校读者我要写书评

暂无评论

Femur Bone Volumetric Estimation for Osteoporosis Classification Using Optimization-Based Deep Belief Network in X-Ray Images

引用

COMPUTER JOURNAL 2019年第11期62卷 1656-1670页

作者： Shankar, N. Sathish Babu, S. Viswanathan, C. Saveetha Engn Coll Dept Biomed Engn Chennai 602105 Tamil Nadu India Annamalai Univ Dept Elect & Instrumentat Engn Chidambaram 608002 Tamil Nadu India GRT Inst Engn & Technol Dept Elect & Commun Engn Tiruttani 631209 Tamil Nadu India

Osteoporosis classification is a significant requirement in the medical field to automatically classify the patients with skeleton disorder that occurs as a result of aging. The classification algorithms required improved accuracy and computationally less complexity. Accordingly, this paper proposes a classification method using the proposed gradient harmony search (GHS) optimization-based deep belief network. The GHS is developed by integrating the harmony search (HS) in the gradient descent (GD) algorithm. The osteoporosis classification is progressed as five major steps: preprocessing, segmentation using active shape model, geometric estimation using the proposed template search method, feature extraction for extracting the medical and image level features, and osteoporosis classification using the proposed GHS based deep belief network. The proposed template search method updates the geometric points of the femur segment effectively and automatically. Experimentation using the real-time database ensures the effectiveness of the proposed method in terms of accuracy, sensitivity, and specificity. The proposed method acquired the accuracy of 0.9539, proving that the osteoporosis classification using the proposed algorithm seems to be effective in taking accurate decisions regarding the patients.

关键词： femur bone osteoporosis classification deep belief network harmony search algorithm gradient search algorithm

来源：评论

学校读者我要写书评

暂无评论

Intelligent computation techniques for optimization of the shortest path in an asynchronous network-on-chip

引用

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第1期22卷 335-346页

作者： Ilamathi, K. Rangarajan, P. RMD Engn Coll Chennai Tamil Nadu India

Network-on-chip (NoC) offers itself to be a suitable interconnection structure and as a viable alternative for system-on-chip, and hence is employed in very-large-scale integration (VLSI) design. An asynchronous network-on-chip (ANoC) design has low energy consumption because of the absence of the clock. However, obtaining optimal path routing in an asynchronous network-on-chip poses computational complexities. In this work, the shortest optimal paths are determined by employing five contemporary optimization techniques, including the harmony search (HS) algorithm using the Hopfield neural network (HNN) in an ANoC mesh topology. Using optimal parameters, in an ANoC, the energy consumption is significantly reduced and a faster convergence speed is achieved. The HS technique was found to have the least consumption of energy and time-complexity in the investigated techniques. HS technique outperformed all the other techniques in various aspects, making it the most suitable for determining the optimal shortest path.

关键词： Asynchronous network-on-chip Shortest path harmony search algorithm Energy consumption

来源：评论

学校读者我要写书评

暂无评论

The impact of demand response programs on UPFC placement

引用

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2019年第6期27卷 4624-4639页

作者： Anari, Abbas Sharifi Nasab Ehsan, Mehdi Firuzabad, Mahmud Fotuhi Islamic Azad Univ Dept Elect & Comp Engn Sci & Res Branch Tehran Iran Sharif Univ Technol Dept Elect Engn Tehran Iran

Demand response (DR) and flexible AC transmission system (FACTS) devices can be effectively used for congestion management in power transmission systems. However, demand response program (DRP) implementation can itself affect the optimum location of FACTS devices, which is one of the main issues in power system planning. This paper investigates the impact of DRPs on unified power flow controller (UPFC) placement. The harmony search algorithm is employed to determine the optimum locations and parameter setting of UPFC in a long-term framework. The optimization problem is solved with different objectives including generation and congestion cost reduction, as well as loss reduction. In this paper, the proposed approach is analyzed using 5 different cases, which are defined in such a way that they demonstrate the impact of DRPs on the UPFC placement problem. The IEEE reliability test system is used as an illustrative example to demonstrate the necessity of considering DRPs for UPFC placement.

关键词： FACTS devices demand response programs harmony search algorithm congestion management loss reduction

来源：评论

学校读者我要写书评

暂无评论

Towards Optimization of Metaheuristic algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy

引用

IEEE ACCESS 2019年 7卷 24267-24281页

作者： Kazmi, Saqib Javaid, Nadeem Mughal, Muhammad Junaid Akbar, Mariam Ahmed, Syed Hassan Alrajeh, Nabil COMSATS Inst Informat Technol Islamabad 44000 Pakistan Kyungpook Natl Univ Sch Comp Sci & Engn Daegu South Korea King Saud Univ Coll Appl Med Sci Riyadh 11633 Saudi Arabia

Internet of Things enabled smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining a balance between demand and supply by implementing demand response (DR) program. In SG, the main focus of the researchers is on home energy management (HEM) system, which is called demand side management. Appliance scheduling is an integral part of HEM system as it manages energy demand according to supply, by automatically controlling the appliances and shifting the load from peak to off peak hours. In this paper, the comparative performance of HEM controller embedded with heuristic algorithms, such as harmony search algorithm, enhanced differential evolution, and harmony search differential evolution, is evaluated. The integration of renewable energy source (RES) in SG makes the performance of HEM system more efficient. The electricity consumption in peak hours usually creates peaks and increases the cost but integration of RES makes the electricity consumer able to use the appliances in the peak hours. We formulate our problem using multiple knapsack theory that the maximum capacity of the consumer of electricity must be in the range, which is bearable for consumer with respect to electricity bill. Feasible regions are computed to validate the formulated problem. Finally, simulation of the proposed techniques is conducted in MATLAB to validate the performance of proposed scheduling algorithms in terms of cost, peak-to-average ratio, and waiting time minimization.

关键词： Smart grid knapsack enhanced differential evolution harmony search algorithm home energy management system demand side management

来源：评论

学校读者我要写书评

暂无评论

Economic load dispatch problems with valve-point loading using natural updated harmony search

引用

NEURAL COMPUTING & APPLICATIONS 2018年第10期29卷 767-781页

作者： Al-Betar, Mohammed Azmi Awadallah, Mohammed A. Khader, Ahamad Tajudin Bolaji, Asaju La'aro Almomani, Ammar Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol POB 50 Irbid Jordan Al Aqsa Univ Dept Comp Sci POB 4051 Gaza Palestine Univ Sains Malaysia Sch Comp Sci George Town 11800 Malaysia Fed Univ Wukari Fac Pure & Appl Sci Dept Comp Sci PMB 1029 Wukari Taraba State Nigeria

In this paper, the update process of harmony search (HS) algorithm is modified to improve its concept of diversity. The update process in HS is based on a greedy mechanism in which the new harmony solution, created in each generation, replaces the worst individual in the population, if better. This greedy process could be improved with other updates mechanisms in order to control the diversity perfectly. Three versions of HS have been proposed: (1) Natural Proportional HS;(2) Natural Tournament HS;(3) Natural Rank HS. These three HS versions employed the natural selection principle of the "survival of the fittest". Instead of replacing the worst individual in population, any individual can be replaced based on certain criteria. Four versions of economic loading dispatch (ELD) problems with valve point have been used to measure the effect of the newly proposed HS versions. The results show that the new HS versions are very promising for ELD domain. This claim is proved based on the comparative evaluation process where the new HS versions are able to excel the state-of-the-art methods in almost ELD problems used.

关键词： Economic dispatch Valve point harmony search algorithm Natural update process Optimization

来源：评论

学校读者我要写书评

暂无评论

HSCA: a novel harmony search based efficient clustering in heterogeneous WSNs

引用

TELECOMMUNICATION SYSTEMS 2018年第4期67卷 651-667页

作者： Singh, Surjit Sharma, Rajeev Mohan Natl Inst Technol Kurukshetra Dept Comp Engn Kurukshetra 136119 Haryana India

Clustering objective reasons scalability, fault tolerance, data aggregation or fusion, load balancing of cluster heads, stabilized network topology, maximal network lifetime, increased connectivity, reduced routing delay, collision avoidance and utilizing sleeping schemes in wireless sensor networks. Load balanced clustering effectively organize the network into a connected hierarchy. Clustering is a discrete problem that can have more than one solution under different operating constraints. In this scenario, meta-heuristic algorithms are found suitable because they give set of solutions in acceptable time constraints. In the literature, several analytical and meta-heuristic approaches have been developed for load balanced clustering. In this paper, a novel harmony search based energy efficient load balanced clustering algorithm is presented and it is tested on a large sample network. Results demonstrated that the proposed approach has faster convergence and gives reliable and efficient load balanced clustering as compared to conventional harmony search algorithm (HSA) and several other methods in the literature. Moreover, the robustness of the proposed approach is also verified for different cases of fixed and variable parameters of HSA.

关键词： harmony search algorithm Load balancing Clustering Energy efficiency Convergence Performance modeling

来源：评论

学校读者我要写书评

暂无评论

Minimizing the Total Flow Time for Lot Streaming Flow Shop Using an Effective Discrete harmony search algorithm

Minimizing the Total Flow Time for Lot Streaming Flow Shop U...

引用

7th International Conference on Intelligent Computing (ICIC)

作者： Han, Hong-Yan Liaocheng Univ Coll Math Sci Liaocheng 252059 Peoples R China

ISBN: (纸本)9783642259432

This paper presents a discrete harmony search(DHS) algorithm for solving an n-job,m-machine lot-streaming flowshop scheduling problem(LFSP) with equal-size sublots, the objective is to minimize the total flow time. In the proposed DHS algorithm. The discrete job permutation without any conversion is used in the proposed DHS algorithm. To search for the best sequence,the DHS algorithm uses an effective initialization approach and a novel improvisation strategy. At the same time, an effective local search is embedded. Computational results demonstrate that the proposed DHS algorithm is very effectiveness for the lot-streaming flowshop scheduling problem.

关键词： Lot-streaming flow shop scheduling harmony search algorithm total flow time

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：