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Naïve Bayes Classifier and Particle Swarm optimization Feature Selection Method for Classifying Intrusion Detection System Dataset 3

Naïve Bayes Classifier and Particle Swarm Optimization Feat...

引用

3rd International conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019

作者： Talita, A.S. Nataza, O.S. Rustam, Z. Faculty of Computer Science and Information Technology Gunadarma University Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences University of Indonesia Indonesia

The security of a network might be threatened by an intrusion aim to steal classified data or to find weaknesses on the network. In general, network main security systems use a firewall to control and monitor both incoming and outgoing network traffic. Intrusion Detection System can be used to strengthen network security. Several data mining methods have been used to solve Intrusion Detection System (IDS) problem on a network. On this paper we will use Naïve Bayes Classifier along with Particle Swarm optimization (PSO) as the feature selection method specifically on one of the benchmark dataset on IDS problem, KDD CUP'99. The dataset consists of more than 40 features with more than 400 thousands records. To solve IDS problem on the dataset, it needs a quite expensive cost either on time computation or memory usage hence the use of PSO as the feature selection method. The best classification result was reached when we use 38 features where the accuracy is 99.12%. Particle Swarm optimization method has several parameters that may affect the classification performance. For future improvement, it is possible to use a parameter optimization method to ensure the best classifier performance. © Published under licence by IOP Publishing Ltd.

关键词： Intrusion detection

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Research on Coordinated optimization of Active and Reactive Power in Active Distribution network 3

Research on Coordinated Optimization of Active and Reactive ...

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3rd International conference on Computer Information Science and Application Technology (CISAT)

作者： Wu, Xiaomeng Li, Chong Xian Shiyou Univ Sch Elect Engn Xian Peoples R China Key Lab Measurement & Control Tech Oil & Gas Well Xian Peoples R China

Traditional optimization for distribution network usually uses reactive power optimization to ensure the safe operation of the distribution network, and uses the distributed power and various adjustable resources of active power adjustment to ensure the economic operation of the distribution network. However, in the distribution network, the impedance ratio of the line is large and the coupling of active and reactive power is strong. Unilateral active or reactive optimization for distribution network is not comprehensive. In addition, the uncertainty of Distributed Generation and load poses a great challenge to optimization for active distribution network, the control strategy formulated by traditional deterministic optimization might inaccurate. In this paper, the mathematical model of active and reactive power coordinated optimization for active distribution network is given. Various algorithms dealing with the uncertainty of distribution are introduced, and advantages and disadvantages of various algorithms are analysed.

关键词： Uncertainty analysis

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RNN Based Optimal Sensing Schedule control for Wireless Sensor networks 3

RNN Based Optimal Sensing Schedule Control for Wireless Sens...

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3rd International conference on Artificial Intelligence in Information and Communication (IEEE ICAIIC)

作者： Choi, Seung-Hee Yoo, Sang-Jo Inha Univ Dept Elect & Comp Engn Incheon South Korea

ISBN: (纸本)9781728176383

With the growth of the IoT technologies, the development of WSNs becomes increasingly more important. Since batteries are commonly used as energy sources for sensors in WSNs, high energy efficiency can extend the life of sensors and free them from interference such as energy harvesting. Mobile object tracking is one of the areas where WSNs are used. To save the energy, sensors usually manage multi-mode operation, in which they periodically switch active and inactive modes. There exists a tradeoff between object detection accuracy and energy efficiency. Depending on the object speed, direction and sensor deployment topology, different sensing schedules should be applied. In this paper, we propose a novel RNN-based sensor dynamic duty cycle control method that can determine the optimal sensing schedule of each sensor node. Simulation results show that the proposed model provides accurate object detection performance and achieves high energy efficiency.

关键词： Wireless Sensor network RNN Duty Cycle Object Tracking optimization Machine Learning

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A Novel User Preference Enabling Method for Multi-Objective Look Ahead Power Dispatch

A Novel User Preference Enabling Method for Multi-Objective ...

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Frontiers of Power and Energy (ACFPE), Asian conference on

作者： Nianjie Tian Xiangrui Su Wenfeng Yao Qian Zhao Tengmu Li Jiachen Zhang Power Dispatching and Control Center Guizhou Power Grid Co. Guiyang China Electric Power Researches Institute China Southern Power Grid Co. Guangzhou China School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9798350367676

ISBN: (纸本)9798350378467

To address the challenges of dispatch infeasibility in DC models under high penetration of renewable energy and to better integrate objectives such as renewable energy accommodation, and cost optimization, this paper proposes a multi-objective look-ahead power dispatch model designed for rolling dispatch over a 2-hour time interval. The proposed model considers AC network transmission constraints, AGC regulation capacity, and wind power output characteristics. It is solved using a two-stage hybrid method that combines a user preferences enabling method with a multi-objective metaheuristic method. The effectiveness of the proposed model and method is validated on the IEEE 30-bus test system, demonstrating its capability to manage renewable energy integration, optimize operating costs and carbon emissions, and satisfy power system operation constraints. Numerical studies also highlight the importance of AGC’s real-time adjustment capabilities in accommodating wind power output deviations.

关键词： Renewable energy sources Costs Metaheuristics Automatic generation control Optimal scheduling Carbon dioxide Wind power generation Real-time systems Regulation User preference

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3rd EAI International conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

3rd EAI International Conference on Multimedia Technology an...

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3rd EAI International conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

ISBN: (纸本)9783030825645

The proceedings contain 97 papers. The special focus in this conference is on Multimedia Technology and Enhanced Learning. The topics include: Research on the Method of Eliminating Duplicated Encrypted Data in Cloud Storage Based on Generated Countermeasure network;design of Distributed Hybrid Pipeline Multimedia Aided Scheduling System;intelligent Scheduling of Distributed Displacement Pipeline Based on Hybrid Discrete Drosophila optimization Algorithm;research on Grid Planning Method of Distribution network Based on Artificial Intelligence Technology;intelligent Monitoring Method for Backstage Data Security of Tourism Information Promotion Platform Based on Cloud Computing;preface;research on Multithreaded Data Scheduling control Method for Power Communication Based on Wireless Sensor;research on Industrial Product Modeling Design Method Based on Deep Learning;a Frequency Conversion Circuit for Piezoelectric Vibrating Energy Harvesting;an Adaptive optimization Strict Reverse Navigation Algorithm for Ship Fine Alignment Process;research on Load Feature Extraction Method of Typical Users Based on Deep Learning;enterprise Financial Risk Early Warning System Based on Catastrophe Progression Method;research on Transportation Route Planning Method of Regional Logistics network Based on Transfer Learning;simultaneous Localization of Multiple Defects in Software Testing Based on Reinforcement Learning;Design of Embedded network Human Machine Interface Based on VR Technology;Design of Information Security System Based on JSP Technology and Reinforcement Model;sliding Mode Adaptive control for Sensorless Permanent Magnet Synchronous Motor;recognition Method of Metal Material Pitting Defect Based on Visual Signal Processing;an Improved Detection Method of Safety Helmet Wearing Based on CenterNet;influence Maximization Based on True Threshold in Social networks;arabic Question-Answering System Using Search Engine Techniques.

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Conceptual Design of Wireless Smart Grid for the optimization of Electric Transmission in Iraq

Conceptual Design of Wireless Smart Grid for the Optimizatio...

引用

Computing and Information Technology (ICCIT-1441), 2020 International conference on

作者： Aeshah Burhan Abbas Akram A. Almohammedi Mohammed Balfaqih Sam Darshi Electrical & Electronics Engineering Department Karabük University Karabük Turkey Electrical & Electronics Department Karabük University Karabük Turkey Automobile Transportation Department South Ural State University Chelyabinsk Russia Department of Computer and Network Engineering University of Jeddah Jeddah Saudi Arabia Department of Electrical Engineering Indian Institute of Technology Ropar Punjab India

Rapid development of technology has resulted in a considerable increase in electricity consumption, which has created a barrier not only because of the generation but also in delivery. Thus, when demand increases, the complexity of the electrical network increases as a result of the increased need for improved dependability, efficiency, protection, energy, and environmental sustainability. According to the world bank statistics, Iraq's loss was 51% during distribution, and it is considered significantly high. This study proposes a wireless network-based design for detecting and optimizing Iraq's electricity distribution infrastructure. Moreover, the suggested module is composed of several data gathering methods that are required for the various paths of the power distribution systems. This design offers viable support for a variety of issues confronting Iraq's power distribution systems, including variable voltage levels caused by fluctuating electrical usage, power burglary, manual invoicing, and transmission line breakdowns. The suggested design is intended for use with single-phase power transmission systems; however, it may be adapted for use with three-phase power distribution systems with slight improvements. The introduction of this method will result in significant energy savings, allowing for the availability of electricity to a greater number of users than previously possible in a crowded place. The suggested smart grid design, which was created for the Iraq context, permits real-time control of energy consumption, optimal electricity consumption, minimal loss, diagnosis of power failures, breakdowns, and automatic invoicing.

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3rd EAI International conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

3rd EAI International Conference on Multimedia Technology an...

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3rd EAI International conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

ISBN: (纸本)9783030825614

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Research on the Application of Distributed Consensus control in Microgrids

Research on the Application of Distributed Consensus Control...

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Advanced Electrical and Energy Systems (AEES), International conference on

作者： Rui Zhang Mingche Li Zongjie Fang Lihui Qiao School of New Energy and Power Engineering Lanzhou Jiaotong University Lanzhou China

Appropriate and effective control measures are the key to realizing the safe, reliable and economic operation of the microgrid. From the viewpoint of energy optimization management and system voltage frequency coordination, a hierarchical control architecture for the microgrid is proposed. On this basis, to adapt to the characteristics of distributed energy, improve energy utilization and realize collaborative control, the multi-agent network consistency theory is introduced to make the microgrid plug and play and operate stably. This paper introduces the hierarchical control architecture of microgrids, expounds on the related problems of consistency theory, and explains its application in detail. The research on the application of distributed consistency control in a microgrid is the premise to ensure the safe, stable and reliable operation of the system, and also lays an important foundation for solving other problems in the microgrid.

关键词： Economics Microgrids Reliability theory Consensus control control systems Voltage control Energy management

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SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions 3

SEAGuL: Sample Efficient Adversarially Guided Learning of Va...

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3rd Annual conference on Learning for Dynamics and control (L4DC)

作者： Landry, Benoit Dai, Hongkai Pavone, Marco 496 Lomita Mall Stanford CA 94305 USA 4440 El Camino Real Los Altos CA 94022 USA

Value functions are powerful abstractions broadly used across optimal control and robotics algorithms. Several lines of work have attempted to leverage trajectory optimization to learn value function approximations, usually by solving a large number of trajectory optimization problems as a means to generate training data. Even though these methods point to a promising direction, for sufficiently complex tasks, their sampling requirements can become computationally intractable. In this work, we leverage insights from adversarial learning in order to improve the sampling efficiency of a simple value function learning algorithm. We demonstrate how generating adversarial samples for this task presents a unique challenge due to the loss function that does not admit a closed form expression of the samples, but that instead requires the solution to a nonlinear optimization problem. Our key insight is that by leveraging duality theory from optimization, it is still possible to compute adversarial samples for this learning problem with virtually no computational overhead, including without having to keep track of shifting distributions of approximation errors or having to train generative models. We apply our method, named SEAGuL, to a canonical control task (balancing the acrobot) and a more challenging and highly dynamic nonlinear control task (the perching of a small glider). We demonstrate that compared to random sampling, with the same number of samples, training value function approximations using SEAGuL leads to improved generalization errors that also translate to control performance improvement.

关键词： Adversarial learning Value function approximation Trajectory optimization Model predictive control

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optimization Algorithm-Based Artificial Neural network control of Nonlinear Systems 3rd

Optimization Algorithm-Based Artificial Neural Network Contr...

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3rd International conference on Innovative Computing and Communication, ICICC 2020

作者： Srivastava, Vishal Srivastava, Smriti Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Sector-3 DwarkaNew Delhi India

ISBN: (纸本)9789811551123

For control of various nonlinear systems, many controllers have been developed over a period of time. Most of the plants are either nonlinear or their parameters vary with time. PID controller has limitations as it is unable to handle complex nonlinearities as well as parameter variations in plants. Therefore, a suitable controller needs to be designed for these plants. Artificial neural network (ANN) has capability to handle these complex issues. In this paper, teacher learning-based algorithm (TLBO) has been used with ANN which optimizes the controller parameters and adapts the nonlinearities present in the plants. To analyze the performance, TLBO with ANN controller is used on various systems, i.e., inverted pendulum and a plant discussed in [1]. The simulation results show the plant output versus mean square error (MSE). © 2021, Springer Nature Singapore Pte Ltd.

关键词： Neural networks

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