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IAENG International Journal of Computer Science 2021年第2期48卷 1-14页

作者： Chen, Gonggui Zhang, Ao Zhao, Chenxu Zhang, Zhizhong Professor of Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China A master degree candidate of Chongqing University of Posts and Telecommunications Chongqing400065 China Co. Ltd Inner Mongolia Power Economy and Technology Research Institute Hohhot010010 China A professor of Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China

The distribution of power flow can be effectively improved by optimizing the configuration of Distributed Generators (DGs) and Shunt Capacitors (SCs). Proper placements and capacities of DGs or SCs for real power loss minimization at the radial distribution network (RDN) is attracting more attention as people become more and more dependent on electric power resources. In order to overcome the slow convergence and poor effect of intelligent algorithms in this problem, Particle Swarm Optimization with Orientation and Shrinking factor (PSO-OS) is proposed in this paper. In the suggested PSO-OS algorithm, sensitivity analysis sort of distribution network is introduced to guide the direction of variation to simplify the search space, and shrinking factor is introduced to balance search capabilities in various RDN systems. The proposed method is applied to IEEE-33, IEEE-69 and IEEE-119 systems to solve the problem of simultaneous allocation of DGs and SCs. Simulation results show that the energy loss of the system is reduced and the stability is improved after reconfiguration. By repeating the experiment independently with the traditional PSO algorithm, the comparative analysis of the results proves the superior performance of the improved algorithm. By comparing with the results in recent literature, it reveals the effectiveness of the proposed PSO-OS algorithm in finding the optimal position and capacity of DGs and SCs in the distribution network. © 2021. All Rights Reserved.

关键词： Sensitivity analysis

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Received Power Prediction for Suburban Environment based on Neural network

Received Power Prediction for Suburban Environment based on ...

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International Conference on Information networking

作者： Lina Wu Danping He Ke Guan Bo Ai César Briso-Rodríguez Tianyun Shui Chenji Liu Liju Zhu Xiaopeng Shen State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Systems and Telecommunications Engineering Technical University of Madrid Madrid Spain Radio Network Optimization Center Jiangxi Mobile Communication Company Limited China Overseas consulting co. ltd China international engineering consulting corporation Beijing China

ISBN: (数字)9781728141992

ISBN: (纸本)9781728142005

Accurate received power prediction is important to wireless network planning and optimization, and appropriate channel modeling approach is highly demanded. The existing channel modeling approaches mainly include deterministic models and stochastic models. The deterministic models usually require detailed three-dimensional (3D) environment model including geometry and material information. The stochastic models are based on mathematical expressions which are difficult in describing complex environments. For mountaineous and suburban scenarios, where the environment is complex and difficult to reconstructed, both channel modeling approaches are limited. In this work, back propagation (BP) neural network which is the most widely used artificial neural network (ANN), is employed to accurately predict received power in the suburban scenario. An environmental feature is defined, which can describe the propagation environment only by using limited environmental types instead of complex 3D environment reconstruction. Furthermore, the low-dimensional environmental feature is generated by principal component analysis (PCA). From the measurements, the information of base station (BS) and the receiver (Rx), including 3D locations, frequency, transmitted power, angle information of antenna, and the received power of all the locations are obtained. The information of BS and Rx is combined with environmental features to form datasets for ANN training and testing. The training samples are randomly selected with different percentage from the formed datasets. The mean error, standard deviation and the prediction accuracy of BP networks are explored in the work, which will help researchers to carry out network planning and communication system design.

关键词： Mathematical model Feature extraction Training Predictive models Principal component analysis Neural networks Three-dimensional displays

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Solving optimal power flow using cuckoo search algorithm with feedback control and local search mechanism

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2019年第2期46卷 321-331页

作者： Chen, Gonggui Yi, Xingting Zhang, Zhizhong Qiu, Shiyuan Key Laboratory of Network control and Intelligent Instrument Chongqing University of Posts and Telecommunications Ministry of Education Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Software Technology Co. Ltd Suzhou215000 China

Cuckoo search (CS) algorithm is a novel heuristic algorithm, which can effectively solve the optimization problem by simulating the brood parasitism of some cuckoo species and combining with Lévy flight mechanism. However, it has also been shown to have certain weaknesses, especially falling into local optimums. Therefore, a novel CS algorithm with feedback control and local search mechanism (FLCS) is proposed in this paper. In the FLCS, feedback control is introduced to enhance the efficiency of search process, and local search mechanism is guided by the global optimal solution for improving the poor local search ability of CS method. To verify the performance of our approach, 21 test functions of different types are first employed. Then, the FLCS has been performed on the IEEE 30-bus power flow test case for optimal power flow (OPF) problem with valve point effect. The results indicate that the proposed FLCS method clearly has better performance than CS in the solution accuracy and convergence speed. In addition, the comparison results show that FLCS performs better than other evolutionary methods from literature for different functions. © International Association of Engineers.

关键词： Feedback control

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Multi-objective Improved Bat Algorithm for optimizing fuel cost, emission and active power loss in power system

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2019年第1期46卷 118页

作者： Chen, Gonggui Qian, Jie Zhang, Zhizhong Sun, Zhi Key Laboratory of Network Control and Intelligent Instrument Chongqing University of Posts and Telecommunications Ministry of Education Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Guodian Enshi Hydropower Development Enshi445000 China

In this paper, a new multi-objective improved bat algorithm (MOIBA) is proposed to solve the constrained multi-objective optimal power flow (MOOPF) problem with contradictory objectives. The proposed MOIBA algorithm, introducing nonlinear inertia weight, global optimal guiding mechanism and monotone random filling model based on extreme (MRFE), can improve the shortcomings of basic bat algorithm which is easy to fall into local optimum. A Pareto-dominant method with constraint priority (PMC) is proposed to ensure that state variables can satisfy the inequality constraints of MOOPF problem. To obtain well-distributed Pareto optimal set (POS), an elite non-dominated sorting method with crowding-distance (ESCD) isadopted. In addition, a fuzzy affiliation approach (FAA) is used to select the best compromise (BC) from the obtained POS. The IEEE 30-bus, IEEE 57-bus and IEEE 118-bus systems are employed to evaluate the effectiveness of MOIBA with four objectives, which includes optimizing basic fuel cost and emission concurrently, optimizing basic fuel cost and active power loss concurrently, optimizing fuel cost with value-point loadings and active power loss concurrently, optimizing basic fuel cost, emission and active power loss concurrently. The legion experimental results obtained by MOIBA, which are contrast to MOPSO and MODE algorithms, validate that MOIBA has definite competitive advantages to achieve satisfactory POS. Furthermore, two performance metrics, generational distance (GD) and spacing (SP), are chosen to estimate the distribution and diversity of Pareto solutions obtained by MOIBA. © International Association of Engineers.

关键词： Electric load flow

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Research on hybrid modified cuckoo search algorithm for optimal reactive power dispatch problem

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2018年第2期45卷 328-339页

作者： Chen, Gonggui Lu, Zhengqin Zhang, Zhizhong Sun, Zhi Key Laboratory of Network control and Intelligent Instrument Chongqing University of Posts and Telecommunications Ministry of Education Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Guodian Enshi Hydropower Development Enshi445000 China

In this paper, an efficient and reliable approach based on hybrid modified cuckoo search algorithm (MCS) combining with differential evolutionary algorithm (DE) (named MCS-DE) is proposed to solve optimal reactive power dispatch (ORPD) problem with minimization of power losses (Ploss), voltage stability index (Lindex) and voltage deviation (Vd) as objectives. The original CS method often converges to local optima. In order to avoid this shortcoming, a series of modifications is purposed to the assimilation policy rule of CS. The variations of the two main parameters and an improved search equation are introduced into the MCS-DE to improve local search near the global best, and it profits from DE to further improve the optimization performance. The proposed MCS-DE is examined and implemented on IEEE 30-bus and IEEE 57-bus test power systems with three different objectives. The simulation results presented in this paper demonstrate the effectiveness and robustness of hybrid MCS-DE approach for solving ORPD problem and it can be made better results compared to the CS, DE, and other methods reported in the literature as demonstrated by simulation results. © International Association of Engineers.

关键词： Optimization

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Quasi-oppositional cuckoo search algorithm for multi-objective optimal power flow

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2018年第2期45卷 255-266页

作者： Chen, Gonggui Qiu, Siyuan Zhang, Zhizhong Sun, Zhi Key Laboratory of Network control and Intelligent Instrument Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Guodian Enshi Hydropower Development Enshi445000 China

This paper introduces the multi-objective cuckoo search (MOCS) method for solving the multi-objective optimal power flow (MOOPF) which is a multi-variable, multi-constraint and nonlinear programming problem. In order to speed up convergence and enhance the quality of solution, the quasi-opposition based learning mechanism is adopted to propose the multi-objective quasi-oppositional cuckoo search (MOQOCS) algorithm in this paper. In MOCS and MOQOCS methods, the feasibility-prior domination principle (FDP) is presented to ensure the feasibility of simulation result which is based on the objective values and the sum of constraint violation values. The crowding-distance sorting is considered to enhance the diversity of Pareto-optimal solutions and obtain better distributed Pareto optimal front. IEEE 30-bus and IEEE 57-bus systems have been considered to check the performance of the proposed methods. The simulation results confirm that MOQOCS algorithm obtains superior compromise solution and produces better distributed Pareto optimal front compared to other methods. © International Association of Engineers.

关键词： Nonlinear programming

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Modified Firefly Algorithm for Handling Optimal Power Flow control with Operational Constraints

Modified Firefly Algorithm for Handling Optimal Power Flow C...

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Chinese Automation Congress

作者： Gonggui Chen Xingting Yi Zhizhong Zhang College of Automation Chongqing University of Posts and Telecommunications Chongqing China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecomm unications Chongqing China

This study describes firefly algorithm (FA) to solve optimal power flow (OPF) control with satisfying various operational constraints. Due to firefly algorithm is easy to convergence prematurely and has the inferior solving skills, thus, modified firefly algorithm (MFA) is formed by combining the dimensional-based approach with levy flight, which is incorporated in original FA. The proposed MFA approach is implemented on IEEE 30-bus system for solving optimal power flow control. Besides, the results obtained by the MFA algorithm are comparable with those of FA and PSO. The numerical results demonstrate the capabilities of the MFA algorithm to generate true and well-distributed solutions of the OPF control. The simulation results also show that the MFA produces better quality of the solutions than other algorithms. This learning can be more beneficial to the further research of optimal power flow control.

关键词： Optimal power flow Firefly algorithm Levy flight IEEE30

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2-9 Wireless communication technology for small unmanned aircraft systems ~towards the deployment of iot in the sky~

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Journal of the National Institute of Information and communications Technology 2017年第2期64卷 57-70页

作者： Miura, Ryu Ono, Fumie Kagawa, Toshinori Shan, Lin Tsuji, Hiroyuki Li, Huan-Bang Matsuda, Takashi Takizawa, Kenichi Kojima, Fumihide Wireless Networks Research Center Mobile communication Wireless control communication Japan Wireless Systems Laboratory Wireless Networks Research Center Mobile communication Japan Wireless Systems Laboratory Wireless Networks Research Center Wireless control communication Japan Japan Strategic Program Produce Office Social Innovation Unit Mobile communication Japan Japan Wireless Systems Laboratory Wireless Networks Research Center Wireless sensor network Japan Wireless Systems Laboratory Wireless Networks Research Center Mobile communication Under water communication Japan Wireless Systems Laboratory Wireless Networks Research Center Wireless communcation Japan

The "aerial industrial revolution" is widely expected, in which the small unmanned aircrafts, or "drones", are becoming popular in aerial photography and videography, survey, logistics, and disaster management. However, the safety of the drones is still not sufficient and it is said to be essential for future development of the industrial market. For safety control and telemetry, the reliable radio communication is indispensable. However, the most of the current drones use the radio technology used in radio control toys. We introduced small fixed-wing unmanned aircrafts four years ago aiming to develop "an aerial radio tower" for large-scale disaster situations, and have carried out field trials and radio propagation measurements and analysis. Moreover, based on those experience and its know-hows, we have also promoted R&D on wireless technologies for reliable operation of drones, including multi-rotors, which is necessary for their future growth of industrial applications. We will further extend and develop those technologies for contribution to aerial IoT and aerial industrial revolution. © 2017 National Institute of Information and communications Technology. All rights reserved.

关键词： Drones

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2-7 Development and field trial of D2D networks for local area information collection and distribution

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Journal of the National Institute of Information and communications Technology 2017年第2期64卷 43-51页

作者： Li, Huan-Bang Shan, Lin Miura, Ryu Matsuda, Takashi Kojima, Fumihide Owada, Yasunori Inoue, Masugi Japan Japan Wireless Networks Research Center Mobile communication Wireless control communication Japan Wireless Systems Laboratory Wireless Networks Research Center Wireless sensor network Wireless power transmission Japan Wireless Systems Laboratory Wireless Networks Research Center Wireless communcation Japan Applications Laboratory Resilient ICT Research Center Distributed system Wireless access network Japan International Research Advancement Office Global Alliance Department Wireless network Japan

NICT has developed a testbed of device-to-device communication networks for the purposes of information collection and distribution among local communities. With the cooperation of local administrations, the testbed was deployed in the Odaiba area of Minato City of Tokyo as well as in Seika Town of Kyoto, respectively, in 2014. The Odaiba area and Seika Town are respectively used as a typical urban model and a typical rural model. All devices of the testbed are installed at 920 MHz frequency band. On one hand, various devices of the testbed are installed in the community buses including 'Odaiba Rainbow Buses' operated by Minato City as well as 'Seika Kururin Buses' operated by Seika Town. On the other hand, devices of the testbed are deployed in the surroundings of bus routes. Various experiments have been being conducted since then. None of devices performs central coordination in the testbed. Devices communicate each other autonomously when they are within communication range. Consequently, any single device doesn't have dominant effect to the entire network. Such features enable robust communication networks during emergency situation such as disasters. Devices installed in buses communicate with surrounding devices anywhere within range and exchange information each other, so that local area information are collected and distributed as buses move. Moreover, by receiving the location information sent from the running buses across all bus routes, we construct a bus location guidance system. The developed device-to-device communication networks for information sharing at local community are independent from cellular and other existing wireless networks and various applications can be expected. © 2017 National Institute of Information and communications Technology. All rights reserved.

关键词： Buses

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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