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Review of feasibility wind turbine technologies for highways energy harvesting

Journal of Physics: Conference Series 2020年第1期1432卷

作者： H F Liew I Baharuddin Abd R Rosemizi I Muzamir S I S Hassan Faculty of Engineering Technology University Malaysia Perlis Sungai Chuchuh 02100 Padang Besar (U) Perlis Malaysia. School of Electrical System Engineering Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia. School of Computer and Communication Engineering. Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia.

Wind energy is one of the non-conventional forms of energy and it is available in affluence. It is also claimed that the wind power is pollution-free, replacement of fossil fuel and that its source of energy is freely available. Electricity can be generated with the help of a wind turbine generator. In this paper, a comprehensive study on contemporary portable wind energy harvesters has been conducted. The different existing performance such as reliability evaluation models, various problems related to structure wind turbine components (blade, gearbox, generator and transformer) and grid for wind energy system have been discussed. At the same time, experimental analysis is focused on behaviour, especially characteristics of impact wind energy, performance as lots of advanced research work has already been done or going on the harnessing of natural wind energy. In this review paper, a different model wind turbine has been studied from previous testing purpose presented. This review aim of utilizing this wind energy in a most effective manner to get the maximum electric output, and therefore the government can think over implementing the suitable type of wind turbine configuration selected highway at low cost as our installation site taking the advantage of the moving vehicles on both sides of the road.

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Analysis of possibilities of alleviating repercussions caused by large disturbances in the power system

Analysis of possibilities of alleviating repercussions cause...

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Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018)

作者： Robert Noskov Ivica Petrović Hrvoje Glavaš Damir Šljivac Tomislav Barić Croatian Transmission System Operator Ltd. Vukovarska cesta 217 31000 Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Ulica Kneza Trpimira 2b 31000 Osijek Croatia

ISBN: (纸本)9781839531330

Various EU regulations have established rules for accessing the electricity exchange grid in order to ensure proper functioning of the electricity market while maintaining a proper level of system security. system security depends on the technical capabilities of its components to withstand disturbances and to help prevent serious interruptions or to re-establish system operation after a breakdown occurs. This paper generally gives a theoretical and practical overview of measures for the automatized protection against voltage disruption and reduction of the active or reactive load of lines or transformers in the subsystem PrP Osijek. In addition to automatic protection, measures of excluding certain elements of the grid will be shown, as well as functions for blocking/activating the regulation of grid elements in order to reduce active and reactive loads of lines or transformers. The analysis gives the effect of some measurements on a real transmission grid model. The model had to be adjusted with the grid state and load requirements that anticipated various unfavourable scenarios, which could cause the power system to break down.

关键词： EES AUTOMATED PROTECTION DISTURBANCES

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Exploring interaction’s quality attributes at Mobile Government services

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Journal of Physics: Conference Series 2019年第1期1339卷

作者： Abdulla, Jaafar Mohamed Mohd Khalit Bin Othman Suraya Binti Hamid Ali Hussein Zolait Norliya binti Ahmad Kassim Faculty Of Computer Science And Information Technology University of Malaya Kuala Lumpur Malaysia Department Of Information System University of Malaya Kuala Lumpur Malaysia College Of Information Technology University of Bahrain Sakheer Kingdom of Bahrain Faculty of Information Management Universiti Teknologi MARA (UiTM) Shah Alam Malaysia

Popularity of smart devices among people leads organizations from different sectors to extend the channels of service delivery to maximize total beneficiaries. Mobile Government is one of these extended channels that use nowadays by government sector to allow end users performing the transactions with less time and efforts. Main features of mobile government services are the mobility which enables the public to perform their transactions online at anywhere and anytime. Dealing with smart devices for online services has limitations that need to be considering by the service provider to be sure that the delivered services meet the end users’ perspective. To measure satisfaction of m-government services, it required a compatible measurement scale that fits with the environment of such services. Using other S.Q. measurement’s scale (i.e., e-commerce, e-services, e-government) at the context of m-government leads to difficulties analysis of the service delivery process and inaccurate results. However, there’s a lack of service quality framework at the context of mGovernment services which is important nowadays to construct a compatible and suitable service quality measurement’s scale that must contain quality attributes that reflecting the environment of m-government. From this point, it encourages the researchers at the current paper to analyze the concept of mGovernment S.Q. with particular focusing on “interaction” attribute. This study uses a systematic literature reviews in the related fields of electronic S.Q., human-computer interactions, and mobile government services, which guided the researcher to identify the related sub-dimensions of interaction. Study finds that the sub-dimensions of interactions’ quality are: 1) User control, 2) Synchronicity, 3) Two-way communication, and 4) Responsiveness.

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Face recognition system Using Deep Neural Network with Convolutional Neural Networks

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Journal of Physics: Conference Series 2019年第1期1235卷

作者： Erick Fernando Denny Andwiyan Dina Fitria Murad Derist Touriano Muhamad Irsan Information System Department School of Information Systems Bina Nusantara University Indonesia Universitas Islam Syekh Yusup (UNIS) School of Information Technology Indonesia Information System Department Binus Online Learning Bina Nusantara University Indonesia Information Technology Department Faculty of computer science and engineering University of Adi Wangsa Indonesia

Face recognition has long been a hot topic and challenging research point in areas such as image processing, pattern recognition, and machine vision. The face is a biometric feature with the intrinsic nature of a human. So that the face has self-stability, deep individual differences and can be an ideal basis for verification of an identity. In this research use, Deep Learning Network method uses to perform detection or face recognition. In this study, we present a framework that can be used to detect faces. This research is also able to present a DNN model that is used to study data sources from the data stream in sequence. The most important part of this study is able to adjust the capacity of the model from the simple one. This research uses experimental design method. The first step is a collection of face image data. Then the architecture design starts from the determination of the depth of the network, layout layers, and the selection of layer types that will be used to get the model based on input dataset and label name index.

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Global, regional, and national age-sex-specific burden of diarrhoeal diseases, their risk factors, and aetiologies, 1990-2021, for 204 countries and territories: a systematic analysis for the Global Burden of Disease Study 2021

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LANCET INFECTIOUS DISEASES 2025年第5期25卷 519-536页

作者： Kyu, Hmwe Hmwe Vongpradith, Avina Dominguez, Regina-Mae Villanueva Ma, Jianing Albertson, Samuel B. Novotney, Amanda Khalil, Ibrahim A. Troeger, Christopher E. Doxey, Matthew C. Ledesma, Jorge R. Sirota, Sarah Brooke Bender, Rose Grace Swetschinski, Lucien R. Cunningham, Matthew Spearman, Sandra Abate, Yohannes Habtegiorgis Abd Al Magied, Abdallah H. A. Abd ElHafeez, Samar Abdoun, Meriem Abera, Bayeh Abidi, Hassan Aboagye, Richard Gyan Abtew, Yonas Derso Abualruz, Hasan Abu-Gharbieh, Eman Abukhadijah, Hana J. Aburuz, Salahdein Addo, Isaac Yeboah Adekanmbi, Victor Adetunji, Charles Oluwaseun Oluwaseun Adeyeoluwa, Temitayo Esther Adhikary, Ripon Kumar Adnani, Qorinah Estiningtyas Sakilah Adra, Saryia Adzigbli, Leticia Akua Afolabi, Aanuoluwapo Adeyimika Afzal, Muhammad Sohail Afzal, Saira Agampodi, Suneth Buddhika Agide, Feleke Doyore Ahinkorah, Bright Opoku Ahmad, Aqeel Ahmad, Sajjad Ahmed, Ali Ahmed, Ayman Ahmed, Haroon Ahmed, Saeed Akinosoglou, Karolina Akter, Ema Al Awaidy, Salah Alajlani, Muaaz M. Alam, Khurshid Albakri, Almaza Albashtawy, Mohammed Aldhaleei, Wafa A. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Syed Shujait Ali Ali, Waad Alif, Sheikh Mohammad Aljunid, Syed Mohamed Al-Marwani, Sabah Almazan, Joseph Uy Al-Mekhlafi, Hesham M. Almustanyir, Sami Alqahatni, Saleh A. Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Altaf, Awais Altirkawi, Khalid A. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Alyahya, Mohammad Sharif Ibrahim Al-Zyoud, Walid A. Amugsi, Dickson A. Andrei, Catalina Liliana Antoni, Sebastien Anuoluwa, Boluwatife Stephen Anuoluwa, Iyadunni Adesola Anwari, Saleha Anwar Palwasha Apostol, Geminn Louis Carace Arabloo, Jalal Arafat, Mosab Aravkin, Aleksandr Y. Areda, Demelash Aregawi, Brhane Berhe Aremu, Abdulfatai Arndt, Michael Benjamin Asgedom, Akeza Awealom Ashraf, Tahira Athari, Seyyed Shamsadin Atreya, Alok Ayele, Firayad Azadi, Davood Azhar, Gulrez Shah Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Taghanaki, Pegah Bahrami Bahramian, Saeed Balakrishna Department of Health Metrics Sciences School of Medicine Institute for Health Metrics and Evaluation University of Washington Seattle 98195 WA United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Center for Biostatistics Ohio State University Columbus OH United States Department of Global Health University of Washington Seattle WA United States Urban Indian Health Institute Seattle Indian Health Board Seattle WA United States School of Medicine Yale University New Haven CT United States Department of Clinical Governance and Quality Improvement Aleta Wondo General Hospital Aleta Wondo Ethiopia College of Pharmacy Ajman University Ajman United Arab Emirates Department of Epidemiology Alexandria University Alexandria Egypt Department of Medicine University of Sétif Algeria Sétif Algeria Department of Health Sétif Algeria Department of Medical Microbiology Bahir Dar University Bahir Dar Ethiopia Department of Biology Ghent University Ghent Belgium Laboratory Technology Sciences Department Yasuj University of Medical Sciences Yasuj Iran Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Department of Biomedical Science Arba Minch University Arba Minch Ethiopia Department of Nursing Al Zaytoonah University of Jordan Amman Jordan Amman Jordan Department of Clinical Sciences Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center-Academic Health System Hamad Medical Corporation Doha Qatar College of Pharmacy University of Jordan Amman Jordan Department of Therapeutics United Arab Emirates University Al Ain United Arab Emirates School of Medicine University of Sydney Sydney NSW Australia Centre for Social Research in Health University of New South Wales Syd

Background Diarrhoeal diseases claim more than 1 million lives annually and are a leading cause of death in children younger than 5 years. Comprehensive global estimates of the diarrhoeal disease burden for specific age groups of children younger than 5 years are scarce, and the burden in children older than 5 years and in adults is also understudied. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to assess the burden of, and trends in, diarrhoeal diseases overall and attributable to 13 pathogens, as well as the contributions of associated risk factors, in children and adults in 204 countries and territories from 1990 to 2021. Methods We used the Cause of Death Ensemble modelling strategy to analyse vital registration data, verbal autopsy data, mortality surveillance data, and minimally invasive tissue sampling data. We used DisMod-MR (version 2.1), a Bayesian meta-regression tool, to analyse incidence and prevalence data identified via systematic reviews, population-based surveys, and claims and inpatient data. We calculated diarrhoeal disability-adjusted life-years (DALYs) as the sum of years of life lost (YLLs) and years lived with disability (YLDs) for each location, year, and age-sex group. For aetiology estimation, we used a counterfactual approach to quantify population-attributable fractions (PAFs). Additionally, we estimated the diarrhoeal disease burden attributable to the independent effects of risk factors using the comparative risk assessment framework. Findings In 2021, diarrhoeal diseases caused an estimated 1.17 million (95% uncertainty interval 0.793-1.62) deaths globally, representing a 60.3% (50.6-69.0) decrease since 1990 (2.93 million [2.31-3.73] deaths). The most pronounced decline was in children younger than 5 years, with a 79.2% (72.4-84.6) decrease in diarrhoeal deaths. Global YLLs also decreased substantially, from 186 million (147-221) in 1990 to 51.4 million (39.9-65.9) in 2021. In 2021, an esti

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Boundary Value Analysis Testing on Augmented Reality of Indonesian Fruit Recognition at Mekarsari Tourist Park using Cloud Method on Android Mobile Devices

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Journal of Physics: Conference Series 2019年第1期1196卷

作者： R Dewi Agushinta Hustinawaty Ihsan Jatnika Henny Medyawati Information System Faculty of Computer Science and Information Technology Gunadarma University Jl. Margonda Raya No. 100 Pondok Cina Depok 16424 West Java Informatics Engineering Faculty of Industrial Technology Gunadarma University Jl. Margonda Raya No. 100 Pondok Cina Depok 16424 West Java

Software testing is a process of implementing a program with the aim of finding an error. A good test case is if the test has the possibility of finding an uncovered error. A successful test is if the test finds an error that was not initially found. One of the testing types available is black box testing. This paper proposes testing using black box testing technique. The black box testing method consists of several ways including equivalence partitioning, boundary value analysis, comparison testing, sample testing, robustness testing, and others. Among the many methods of testing, Boundary Value Analysis was chosen in this study. Boundary Value Analysis is a method of testing by determining the value of the lower limit and upper limit of the data that will be tested. This test is performed on the functions of Augmented Reality prototype of Indonesia fruit recognition by using the cloud method on Android mobile devices. From testing the distance of marker objects to Android mobile devices on cloud recognition using an Android camera shows that the higher the augmentable rating of the target image and the more the number of markers features detected, the easier the image will be tracked by AR. If the distance between the camera and the real object gets farther away, then the virtual object cannot be displayed. Testing with mobile devices using HSDPA, 3G and WIFI networks connecting a cloud database server to display virtual objects shows the average results of devices that use WIFI networks provide the fastest performance.

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A novel approach based on deep learning techniques and UAVS to yield assessment of paddy fields 9

A novel approach based on deep learning techniques and UAVS ...

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9th International Conference on Knowledge and systems Engineering, KSE 2017

作者： Tri, Nguyen Cao Duong, Hieu N. Van Hoai, Tran Van Hoa, Tran Nguyen, Vu H. Toan, Nguyen Thanh Snasel, Vaclav Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Viet Solutions of Information System Company Ho Chi Minh City Viet Nam Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic

ISBN: (纸本)9781538635766

Yield assessment is one of the main interests at regional and national levels of agriculture management. The accuracy of the assessment is not highly expected inherently and, moreover, some costly and sophisticated tools (e.g., satellite images) have been usually involved without a careful consideration of their investment. In this paper, a novel approach has been proposed orienting to farmers (especially in Southeastern Asia) who are only affordable for low cost and easy-to-use tools. With this vision, the paper presents an idea to co-operate certain, powerful and modern technologies–deep neural networks (DNNs) and unmanned aerial vehicles (UAVs)–with respect to solving the problem of yield assessment. The imagery of paddy fields acquired by UAVs at low altitudes is then used for training DNNs and assessing the yield of the paddy fields. Four DNN models are applied to figure out the most appropriate one for this approach. To test the applicability of the proposed approach, some experiments are conducted on a dataset which was collected at paddy fields in Tay Ninh province, Vietnam. The yield assessment is not directly predicted from DNNs, instead being achieved by a combination of the classification results and a bush-level yield estimation of agricultural experts in the fields. The paper indicates that the proposed approach is quite potential for precision agriculture, along with some remaining challenges. © 2017 IEEE.

关键词： Deep neural networks

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Smart radio environments

arXiv

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arXiv 2021年

作者： Gradoni, Gabriele Renzo, Marco Di Díaz-Rubio, Ana Tretyakov, Sergei A. Caloz, Christophe Gradoni, Gabriele Peng, Zhen Alu, Andrea Lerosey, Geoffroy Fink, Mathias Galdi, Vincenzo Cui, Tie Jun Frazier, Benjamin W. Anlage, Steven M. Salucci, Marco Massa, Andrea Cheng, Qiang Wang, Jinghe Jin, Shi Dardari, Davide Decarli, Nicoló Yurduseven, Okan Matthaiou, Michail Kenney, Mitchell Gordon, George Georgiou, Orestis Nguyen, Cam Ly Martini, Enrica Maci, Stefano Wakatsuchi, Hiroki Phang, Sendy School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Laboratoire des Signaux et Systémes CNRS CentraleSupélec Université Paris-Saclay Gif-sur-Yvette Paris France Department of of Electronics and Nanoengineering Aalto University Espoo Finland META Research Group KU Leuven Belgium School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham University Park NG72RD United Kingdom Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign IL United States Advanced Science Research Center City University of New York United States Greenerwave 6 rue Jean Calvin Paris75005 France Institut Langevin 1 rue Jussieu Paris75005 France Fields & Waves Lab Department of Engineering University of Sannio Benevento Italy State Key Laboratory of Millimeter Waves Southeast University Nanjing China Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Department of Electrical and Computer Engineering Department of Physics Quantum Materials Center University of Maryland College ParkMD20742 United States Trento Italy Chengdu China Beijing China Institute of Electromagnetic Space State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing China University of Bologna Bologna Italy Bologna Italy Centre for Wireless Innovation Institute of Electronics Communications and Information Technology Queen’s University Belfast Belfast United Kingdom Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Wireless System Laboratory Corporate Research & Development Center Toshiba Corporation Kawasaki Japan Department of Information Engineering an

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Meta-surface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G. © 2021, CC BY.

关键词： Electromagnetic wave propagation

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Maintaining Diversity in an SVM integrated Case Based GA for Solar Flare Prediction

Maintaining Diversity in an SVM integrated Case Based GA for...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yoshio Taniguchi Yoshihiko Kubota Setsuo Tsuruta Yoshiyuki Mizuno Takayuki Muranushi Yuko Hada Muranushi Yoshitaka Sakurai Rainer Knauf Andrea Kutics Hitachi Industry & Control Solutions Ltd. Yokohama Japan School of System Design and Technology Tokyo Denki University Tokyo Japan Faculty for the Study of Contemporary Society Kyoto Women’s University Kyoto Japan RIKEN Advanced Institute of Computational Science Kobe Japan Kwasan and Hida Observatories Kyoto University Kyoto Japan School of Interdisciplinary Sciences Meiji University Tokyo Japan Dept. of Computer Science and Automation Technische Universität Ilmenau Ilmenau Germany Dept. of Natural Sciences International Christian University Tokyo Japan

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Unusually intense solar flares may cause serious calamities such as damages of electric/nuclear power plants. It is thereupon highly demanded, but is quite difficult, to predict intense solar flares due to the imbalanced character of the available data. To cope with this problem, we have heretofore developed and applied a Case Based Genetic Algorithm (CBGALO) that contains a Local Optimizer, which is a Support Vector Machine (SVM). However, the prediction performance significantly depends on input data for learning. Hereupon, CBGALO is further extended by a Case Based automatically restartable Good combination searching GA for both learning features and input data (CBRsGcmbGA). Even the powerful but computationally expensive Deep Learning cannot automatically (evolutionarily, in our approach) search the learning data. Our approach solved this problem a little better by the case-based approach. However, it became obvious that even this work suffers from the typical GA effect in falling into local optima. To improve the results, we hence developed newly a diversity maintenance approach that inserts good individuals with large Hamming distance into the case base as elite individuals in GA's population. In 2 out of 3 classes of solar flares, the performance of our new approach became as high as the best ones among the conventional world top records. Namely, even in those ≥ C class solar flares, our approach applying the Hamming distance to increase diversity had as high a performance 0.662 as compared with the conventional world top record 0.650.

关键词： Genetic algorithms Support vector machines Evolutionary computation Deep learning

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