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Compressing Convolutional Neural networks by L0 Regularization 3

Compressing Convolutional Neural Networks by L0 Regularizati...

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3rd International conference on control, Artificial Intelligence, Robotics and optimization, ICCAIRO 2019

作者： Formanek, Andras Hadhazi, Daniel Department of Measurement and Information Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (纸本)9781728135724

Convolutional Neural networks have recently taken over the field of image processing, because they can handle complex non algorithmic problems with state-of-the-art results, based on precision and inference times. However, there are many environments (e.g. cell phones, IoT, embedded systems, etc.) and use-cases (e.g. pedestrian detection in autonomous driving assistant systems), where the hard real-time requirements can only be satisfied by efficient computational resource utilization. The general trend is training larger and more complex networks in order to achieve better accuracies and forcing these networks to be redundant (in order to increase their generalization ability). However, this produces networks that cannot be used in such scenarios. Pruning methods try to solve this problem by reducing the size of the trained neural networks. These methods eliminate the redundant computations after the training, which usually cause high drop in the accuracy. In this paper, we propose new regularization techniques, which induce the sparsity of the parameters during the training and in this way, the network can be efficiently pruned. From this viewpoint, we analyse and compare the effect of minimizing different norms of the weights (L1, L0) one by one and for groups of them (for kernels and channels). L1 regularization can be optimized by Gradient Descent, but this is not true for L0. The paper proposes a combination of Proximal Gradient Descent optimization and RMSProp method to solve the resulting optimization problem. Our results demonstrate that the proposed L0 minimization-based regularization methods outperform the L1 based ones, both in terms of sparsity of the resulting weight-matrices and the accuracy of the pruned network. Additionally, we demonstrate that the accuracy of deep neural networks can also be increased using the proposed sparsifying regularizations. © 2019 IEEE.

关键词： optimization

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Multi-hop PSO based routing protocol for Wireless Sensor networks with Energy Harvesting 3

Multi-hop PSO based routing protocol for Wireless Sensor Net...

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3rd Annual conference on Information-Communications-Technology-and-Society (ICTAS)

作者： Tukisi, Tlholiso W. Mathaba, Tebello N. D. Odhiambo, Marcel Ohanga Vaal Univ Technol Dept Proc Control & Comp Syst Vanderbijlpark South Africa

ISBN: (纸本)9781538673652

In this paper, three energy efficient routing strategies for a design of a Particle Swarm optimization based Wireless Sensor network (WSN) routing algorithm are presented. The first strategy maximizes the energy of the node with the lowest energy (the worst performing node) in the WSN, the second strategy maximizes the overall WSN energy and the third strategy maximizes the energy of the worst performing node while improving network latency. The best of these strategies is further tested in a WSN with energy harvesting nodes. The results are compared with a benchmark variant of the Low energy adaptive clustering hierarchy (LEACH) protocol, called the LEACH-Centralized Sleeping (CS). The results show that the strategy that maximizes the overall network energy can improve the network lifetime better. The results further show that the energy harvesting aware routing protocol can extend the lifetime of a WSN more than a protocol that is not energy harvesting aware.

关键词： Wireless Sensor networks Energy harvesting PSO Two-tier Clustering LEACH-CS

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Research on optimal control method of distributed generation considering the influence of controllable load 3

Research on optimal control method of distributed generation...

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3rd International conference on Energy Engineering and Environmental Protection (EEEP)

作者： Hu, Bo Wang, Shicheng Yu, Ziheng Wang, Tao Qu, Fei Zheng, Wei Du, Heng Zhou, Bowen State Grid Huludao Elect Power Supply Co Huludao 125000 Peoples R China Northeastern Univ Shenyang 110000 Liaoning Peoples R China

On the basis of optimal allocation of distributed generation in conventional distribution network, and considering the characteristics of active distribution system and the influence of controllable loads, a two-layer optimal configuration model of distributed generation is established. The upper layer model is used to solve the optimal allocation and sizing of distributed power sources for active distribution systems and the lower layer model is used to solve the optimal strategy of controllable loads in each period. The output uncertainty of uncontrollable distributed generators, such as wind power generation and photovoltaic power generation, is characterized by box uncertain set based on robust optimization theory. With this model, the optimal configuration of distributed generation can be solved and the factors of operation and dispatch can be taken into account. To some extent, the overall planning and operation of active distribution system can be realized. Finally, the genetic algorithm is used to solve the two-layer optimization model. The rationality of the proposed model, the applicability of genetic algorithm, and the strong ability of global optimization are verified by case studies of IEEE 33-bus distribution system.

关键词： Distributed power generation

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optimization of underground mine water supply network 3

Optimization of underground mine water supply network

引用

3rd International Symposium on Resource Exploration and Environmental Science, REES 2019

作者： Peng, Ya Jiang, Zhongan School of Civil and Resource Engineering University of Science and Technology Beijing China

A qualified and effective mine water supply system is of great significance for mine dust prevention, mine cooling, fire fighting and other related mining activities that contributing to mine safety. The study in this paper was to improve the efficiency of an underground mine water supply network while taking the water demands, hydraulic conditions, resilience capability and economic cost into consideration. By means of model predictive control technology, an optimal control sequence was computed to minimize a multi-objective cost function that was subject to both physical and operation constrains in the actual network. Comparison of the performance between the original and optimized network was undertaken at a hydraulic condition with typically severe breakdown. Results showed the optimized mine water supply network achieved 95.5% increase for resilience performance with only 17.6% additional investment budget. © Published under licence by IOP Publishing Ltd.

关键词： Groundwater

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3rd EAI International conference on Advanced Hybrid Information Processing, ADHIP 2019

3rd EAI International Conference on Advanced Hybrid Informat...

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3rd EAI International conference on Advanced Hybrid Information Processing, ADHIP 2019

ISBN: (纸本)9783030364014

The proceedings contain 101 papers. The special focus in this conference is on Advanced Hybrid Information Processing. The topics include: Multi-source Heterogeneous Data Acquisition Algorithm Design Different Time Periods;research on Data Security Acquisition System Based on Artificial Intelligence;weak Coverage Area Detection Algorithms for Intelligent networks Based on Large Data;Research on RF Fingerprinting Extraction of Power Amplifier Based on Multi-domain RF-DNA Fingerprint;fault Feature Analysis of Power network Based on Big Data;design of All-Pass Filter System for Power Communication with High Anti-harmonic Interference;improved Design of Classification Algorithm in Cloud Computing and Big Data Environment;research on Dynamic Access control Model of Distributed network Under Big Data Technology;intelligent Data Acquisition Method for Cross-border E-commerce Guidance and Purchase Considering User Demand;Research on Communication Individual Identification Method Based on PCA-NCA and CV-SVM;optimization Design of Cross-Border E-commerce Shopping Guide System Combining Big Data and AI Technology;research on Balanced Scheduling Algorithm of Big Data in network Under Cloud Computing;optimization of Rational Scheduling Method for Cloud Computing Resources Under Abnormal network;design of Agricultural Product Quality and Safety Big Data Fusion Model Based on Blockchain Technology;artificial Intelligence Integration Method for Agricultural Product Supply Chain Quality Data Based on Block Chain;research on Adaptive Scheduling Method of Communication Resource Information in Internet of Things Environment;research on Dynamic network Load Evaluation Algorithm Based on Throughput Monitoring;research on the Classification Method of network Abnormal Data;optimized PointNet for 3D Object Classification;deep Learning Based Adversarial Images Detection.

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Research on Resonant Frequency Feedback control Strategy of EAST Fishtail Divertor Magnet Coil Power Supply 3

Research on Resonant Frequency Feedback Control Strategy of ...

引用

3rd IEEE International Electrical and Energy conference, CIEEC 2019

作者： Zhou, Yu Huang, Yiyun Guo, Fei Sun, Haozhang Hefei Institutes of Physical Science Chinese Academy of Sciences Institute of Plasma Physics Hefei China Chinese Academy of Sciences Institute of Plasma Physics Hefei China University of Science and Technology of China Hefei China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116754

Fishtail divertor (FTD), a new divertor concept, is a significant research object of EAST tokamak divertor system. Considering the requirement of sinusoidal current precision and stable output with variable frequency (10-3800Hz) and adjustable amplitude (0-5000A) in complex and arguable electromagnetic environment, a resonant frequency feedback control strategy is proposed for FTD magnet coil power supply. The equivalent mathematical model of the FTD coil PS and control process is set up. Through detailed theoretical analysis and simulation, the conclusion of performance optimization based on control strategy is obtained. At the work of frequency feedback control strategy, the power supply can promptly identify the resonant network frequency deviation caused by the interference of electromagnetic environment on the equivalent load characteristics within 1.5S, and actively correct the excitation voltage frequency, so as to ensure the accuracy of the FTD magnet coil current. Finally, the correctness of the design is verified through experimental tests. © 2019 IEEE.

关键词： Natural frequencies

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Optimal Multi-Type DG Integration and Distribution System Reconfiguration for Active Power Loss Minimization using CPSO Algorithm 3

Optimal Multi-Type DG Integration and Distribution System Re...

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3rd International conference on control, Automation and Diagnosis, ICCAD 2019

作者： Essallah, Sirine Khedher, Adel Universiteandacute de Sousse Ecole Nationale d'Ingeandacutenieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia

ISBN: (纸本)9781728122922

network reconfiguration and Distributed generation (DG) integration in distribution systems has become one of the major challenging tasks for power utilities. Despite their prospective solutions for distribution system operation in terms of losses minimization and voltage profile enhancement, the inappropriate choice of DG parameters might lead to undesirable effects such as power losses increase and voltage collapse. This paper presents a combined particle swarm optimization (CPSO) based method for optimal multi-type DG integration and network reconfiguration, considering active power loss minimization as an objective function. The DG penetration level is considered in the range of 20% to 50% of total system load. The efficiency of the proposed technique has been tested on the standard IEEE 33-bus distribution system. Numerical results have proven that the proposed CPSO algorithm can efficiently find optimal solutions compared to other competitive methods in the literature. © 2019 IEEE.

关键词： Particle swarm optimization (PSO)

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controlling the Resources of the Intrusion Detection System at network Objects Monitoring

Controlling the Resources of the Intrusion Detection System ...

引用

International conference on Computer Applications & Information Security (ICCAIS)

作者： Nickolay V. Boldyrikhin Olga A. Safaryan Pavel V. Razumov Vitaliy M. Porksheyan Ivan A. Smirnov Denis A. Korochentsev Larissa V. Cherckesova Artem M. Romanov Information System Cybersecurity Department Don State Technical University Rostov-on-Don Russia Applied Mathematics Department Rostov-on-Don Russia Mathematics and Computer Sciences Departmrnt Don State Technical University Rostov-on-Don Russia

ISBN: (数字)9781728142135

ISBN: (纸本)9781728142142

The article is devoted to the optimization of intrusion detection system resources when monitoring a set of network objects. The application of the approach proposed in the article makes it possible to optimally distribute the computing resources of an information system between several objects of a network infrastructure based on the available a priori information about these objects. The scientific novelty lies in the fact that the proposed approach allows us to adapt the mathematical apparatus of the theory of observation control to the tasks of providing information protection for communication networks.

关键词： Monitoring Mathematical model Servers Intrusion detection Computer security Task analysis

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network infrastructure design in connectivity using Inter-VLAN concept in bandung district government 19

Network infrastructure design in connectivity using Inter-VL...

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Proceedings of the 3rd International conference on Telecommunications and Communication Engineering

作者： Aliyya Nur Ramdhania M. Teguh Kurniawan Umar Yunan K. S. Hediyanto Telkom University Dayeuhkolot Bandung

ISBN: (纸本)9781450371803

In recent years the development of communication needed by humans is growing. This is based on the reliability and availability of a communications infrastructure network from a service provider company. The infrastructure can be in the form of a series or topology of devices that support the operation of services, these devices can be physical or virtual. network infrastructure requires a routing protocol to improve the optimization of data communication on data traffic. For the distribution of broadcast domains on network infrastructure, Inter-VLAN can be used to reduce hardware usage and make cost savings. For data packet filtering activities, ACL can be used so that unknown data packets cannot be through the internal network. This research conducted at Bandung District Government is expected to improve the optimization of network infrastructure conditions using Inter-VLAN with the network Development Life Cycle method. With inter-VLAN, 1 broadcast domain on infrastructure at Bandung District Government can be divided into several broadcast domains and each SKPD also can communicate with another. Besides being able to improve performance in Bandung District Government, this can also save costs.

关键词： access control list Inter-VLAN network infrastructure network development life cycle

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Evaluating Particulate Matter (PM2.5 and PM10) Impact on Human Health in Oman Based on a Hybrid Artificial Neural network and Mathematical Models 3

Evaluating Particulate Matter (PM2.5 and PM10) Impact on Hum...

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3rd International conference on control, Artificial Intelligence, Robotics and optimization, ICCAIRO 2019

作者： Alattar, Nebras Yousif, Jabar Sohar University Faculty of Computing and IT Sohar Oman

ISBN: (纸本)9781728135724

The statistics of the World Health Organization (WHO) indicate that outdoor air pollution in 2016 is a significant cause of premature mortality, with an average of 4.2 million death cases. This mortality is due to exposure to PM2.5 particulate matter, which causes many diseases such as respiratory, cardiovascular, and cancers. The concentration of particulate matter (PM) is the most popular air pollutant that affects short term and long term health. The paper aims to study and investigate the concentration dispersion of particulates (PM 2.5 and PM10) and its impact on human health in Oman. The study suggested a hybrid neural and mathematical approaches for analyzing the effect rate of particulate matter (PM2.5 and PM10). The paper implements a comparative study to analyze the proposed neural and mathematical models, which predict the future levels of pollutants in a fast, cheap, and safe way. The Linear regression models achieve fewer results of R, MSE, RMSE (0.7604, 0.0673, 0.2595), respectively. However, the non-linear regression polynomial prediction model obtained excellent results based on the coefficient of determination (R) value of 0.9394 and mean square error (MSE) rate of 0.0209, and root mean square error (RMSE) value of 0.1447. Moreover, the Neural SOM model obtained the highest results in predicting the experimental data that achieved an MSE value of 0.0064, correlation rate (R) value of 0.994, NMSE value of 0.01392, and MAE value of 0.0467. All the results were correctly verified based on suitable mathematical methods. © 2019 IEEE.

关键词： Mean square error

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