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Atom search optimization and its application to solve a hydrogeologic parameter estimation problem

KNOWLEDGE-BASED SYSTEMS 2019年 163卷 283-304页

作者： Zhao, Weiguo Wang, Liying Zhang, Zhenxing Hebei Univ Engn Sch Water Conservancy & Hydropower Handan 056021 Hebei Peoples R China Univ Illinois Illinois State Water Survey Prairie Res Inst Champaign IL 61820 USA

In recent years, various metaheuristic optimization methods have been proposed in scientific and engineering fields. In this study, a novel physics-inspired metaheuristica* optimization algorithm, atom search optimization (ASO), inspired by basic molecular dynamics, is developed to address a diverse set of optimization problems. ASO mathematically models and mimics the atomic motion model in nature, where atoms interact through interaction forces resulting from the Lennard-Jones potential and constraint forces resulting from the bond-length potential. The proposed algorithm is simple and easy to implement. ASO is tested on a range of benchmark functions to verify its validity, qualitatively and quantitatively, and then applied to a hydrogeologic parameter estimation problem with success. The results demonstrate that ASO is superior to some classic and newly emerging algorithms in the literature and is a promising solution to real-world engineering problems. (C) 2018 Elsevier B.V. All rights reserved.

关键词： optimization algorithm Heuristic algorithm Benchmark functions Atom search optimization Global optimization Metaheuristic Parameter estimation

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Collaboration optimization of Flight Schedule in Beijing⁃Tianjin⁃Hebei Airport Group

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Transactions of Nanjing University of Aeronautics and Astronautics 2020年第6期37卷 928-935页

作者： GENG Xi HU Minghua College of Civil Aviation Nanjing University of Aeronautics and AstronauticsNanjing 211106P.R.China Office of Air Traffic Management Civil Aviation Administration of ChinaBeijing 100710P.R.China

The coordinated and integrated development of regional airport group system has been identified as an important research topic in the field of air traffic management in ***,due to the clear limitation on airspace resources and severe traffic congestion,it is necessary to further study the problem of flight schedule coordination optimization for airport *** take the Beijing-Tianjin-Hebei airport Group as an example and construct an optimization model of flight schedule with the minimum adjustment and *** design of the implementation algorithm is *** demonstrated by the simulation results,the flight delay in the Beijing-Tianjin-Hebei multi-airport system is noticeably reduced by applying both the optimization model and the algorithm proposed in this paper.

关键词： air transport flight schedule airport group system optimization algorithm

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optimization of a Sparse Array Antenna for 3D Imaging in Near Range

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IEICE TRANSACTIONS ON ELECTRONICS 2019年第1期E102C卷 46-50页

作者： Lyulyakin, Andrey Chernyak, Iakov Sato, Motoyuki Tohoku Univ Grad Sch Environm Studies Sendai Miyagi 9808579 Japan Tohoku Univ Ctr Northeast Asian Studies Sendai Miyagi 9808576 Japan

In order to improve an imaging performance of a sparse array radar system we propose an optimization method to find a new antenna array layout. The method searches for a minimum of the cost function based on a 3D point spread function of the array. We found a solution for the simulated problem in a form of the new layout for the antenna array with more sparse middle-point distribution comparing with initial one.

关键词： sparse array nearfield imaging array optimization optimization algorithm

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Optimal estimation of initial concentrations and emission sources with 4D-Var for air pollution prediction in a 2D transport model

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SCIENCE OF THE TOTAL ENVIRONMENT 2021年 773卷 145580-145580页

作者： Liu, Caili Zhang, Shaoqing Gao, Yang Wang, Yuhang Sheng, Lifang Gao, Huiwang Fung, J. C. H. Ocean Univ China Coll Ocean & Atmospher Sci Qingdao Peoples R China Ocean Univ China MOE Inst Adv Ocean StudyKey Lab Phys Oceanog Frontiers Sci Ctr Deep Ocean Multispheres & Earth Qingdao Peoples R China Pilot Natl Lab Marine Sci & Technol QNLM Ocean Dynam & Climate Funct Lab Qingdao Peoples R China Int Lab High Resolut Earth Syst Model & Predict i Qingdao Peoples R China Ocean Univ China Minist Educ Key Lab Marine Environm & Ecol Qingdao 266100 Peoples R China Ocean Univ China Minist Educ Frontiers Sci Ctr Deep Ocean Multispheres & Earth Qingdao 266100 Peoples R China Georgia Inst Technol Sch Earth & Atmospher Sci Atlanta GA 30332 USA Hong Kong Univ Sci & Technol Div Environm & Sustainabil Hong Kong Peoples R China

Attributing sources of air pollution events by deploying an efficient observational network is an important and interesting problem in air quality control and forecast studies, but it is very challenging. In order to estimate the sensitivities of pollution events to emission sources, a comprehensive framework is built based on a horizontal 2-dimensional transport model and its adjoint in solving this problem. In an analysis of an idealized air pollution event of PM2.5 over the region of North China, an objective function is defined to optimally estimate the initial concentrations and emission sources through a series of minimization procedures. Results by means of the 4-dimensional variational approach show that, with the optimal initial conditions and emission sources, the model can successfully forecast the pollution event in a few days. The optimal observing network based on sensitivity analysis takes only one third of the cost but greatly retains predictability skill compared to the full-grid observing system, while nearly no predictability skill is detectable if the same number of observational sites is randomly deployed. We evaluate air pollution predictability in the point of focusing on to what degree the root mean square errors between the modeled concentration and the targeted air pollution are limited by the optimal observational network. Results show that air pollution predictability in association with the optimal observational network is limited in the time scales about 6 days. With the high efficiency and in an economic fashion, such a sensitivity-based optimal observing system holds promise for accurately predicting an air pollution event in the targeted area once the adjoint and variational procedure of a realistic atmosphere model including transport and chemical processes is performed. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Transport model Optimal observational network Adjoint sensitivity Air pollution prediction optimization algorithm

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APs Deployment optimization for Indoor Fingerprint Positioning with Adaptive Particle Swarm algorithm 18th

APs Deployment Optimization for Indoor Fingerprint Positioni...

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18th International Conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Zhao, Jianhui Li, Jun Ai, Haojun Cai, Bo Wuhan Univ Sch Comp Sci Wuhan 430072 Hubei Peoples R China Collaborat Innovat Ctr Geospatial Technol Wuhan 430079 Hubei Peoples R China

ISBN: (纸本)9783030050573;9783030050566

Indoor positioning service gives people much better convenience, but its efficiency is affected by the spatial deployment of access points, APs. We propose an algorithm from adaptive particle swarm, APS, and then apply it in APs deployment optimization for fingerprint based indoor positioning. In our method, solutions of APs placement are taken as individuals of one population. Particle swarm method is improved with adaptive technology to ensure the population diversity and also avoid large number of inferior particles. After evolutions, the optimal result is obtained, corresponding to the best solution of APs deployment. The algorithm works well for both single-objective and multi-objective optimizations. Experiments with deployments of 107 iBeacons have been tested in an underground parking lot. Compared with the existing APs placement methods, our APS algorithm can obtain the least indoor positioning error with fixed APs number, while receive the best integrated evaluation considering both positioning error and APs cost with unfixed APs number. The proposed algorithm is easily popularized to the other kinds of indoor spaces and different types of signal sources.

关键词： Indoor positioning APs deployment optimization algorithm Adaptive particle swarm

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Performance Improvement of Antenna Array-Radome System Based on Efficient Compensation and optimization Scheme

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2019年第5期18卷 866-870页

作者： Liu, Lu Nie, Zaiping Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 611731 Sichuan Peoples R China

An efficient scheme with phase compensation and amplitude optimization has been proposed to improve the electromagnetic performance deteriorated by the radome. Instead of altering the configuration of the radome, the phase compensations of the antenna array elements based on the phase variations of the far-field radiated from point sources located at the array grids due to the introduction of the radome have been applied in this approach to calibrate the phase distortion and eliminate the pointing error. On the other hand, the suppression of the sidelobe level and the flash/image lobe level can be achieved by properly adjusting the amplitude of excitation by using thea* optimization algorithm. An amplitude grouping technique has further been used to enhance the feasibility of the proposed optimization scheme. Some examples have been given to show the validity and efficiency of this optimization method.

关键词： Antenna array array-radome system optimization algorithm phased array performance pointing error compensation sidelobe level (SLL) reduction

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Predicting freshwater production in seawater greenhouses using hybrid artificial neural network models

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JOURNAL OF CLEANER PRODUCTION 2021年 329卷

作者： Panahi, Fatemeh Ahmed, Ali Najah Singh, Vijay P. Ehtearm, Mohammad Elshafie, Ahmed Haghighi, Ali Torabi Univ Kashan Fac Nat Resources & Earth Sci Kashan Iran Univ Tenaga Nasl UNITEN Coll Engn Inst Energy Infrastruct IEI Dept Civil Engn Kajang 43000 Selangor Malaysia Texas A&M Univ Zachry Dept Civil & Environm Engn Dept Biol & Agr Engn College Stn TX USA Semnan Univ Dept Water Engn Semnan Iran Univ Malaya UM Fac Engn Dept Civil Engn Kuala Lumpur 50603 Malaysia United Arab Emirates Univ Natl Water & Energy Ctr POB 15551 Al Ain U Arab Emirates Univ Oulu Water Energy & Environm Engn Res Unit Oulu Finland

Freshwater production in seawater greenhouses (SWGH) is an important topic for decision-makers in arid lands. Since arid and semi-arid lands face water shortages, the use of SWGH helps farmers to supply water. This study proposed an integrated artificial neural network (ANN) model, namely, the ANN-antliona* optimization algorithm (ANN-ALO), for predicting freshwater production in a seawater greenhouse. The width, length, and height of the evaporators and the roof transparency coefficient of the SWGH were used as the inputs of the models. The ability of ANN-ALO was benchmarked against the ANN-particle swarm optimization (ANN-PSO), ANN, and ANN-bat algorithms (ANN-BA). The novelties of the current study are the novel hybrid ANN models, the fuzzy reasoning concept for reducing the computational time, the comprehensive analysis of the uncertainty of the parameters and inputs, and the use of non-climate data. Comparing the models' performances in the test phase demonstrated that the ANN-ALO model performed best, with a Root Mean Square Error (RMSE) value that was 18%, 33%, and 39% lower than that of the ANN-BA, ANN-PSO, and ANN models, respectively. For the ANN model, the percent bias (PBIAS) value in the training stage was 0.20, whereas for the ANN-BA, ANN-PSO, and ANN-ALO models, it was 0.14, 0.16, and 0.12, respectively. This study also indicated that the width of the seawater greenhouse was the most important parameter for predicting freshwater production. Furthermore, the results suggested that an evaporator height of 2 m resulted in the highest predicted freshwater production for all the widths except 200 m. The lowest freshwater production for different widths occurred at an evaporator height of 3 m. The generalized likelihood estimation for uncertainty analysis indicated that the uncertainty of the input parameters was lower than that of the model parameters.

关键词： ANN optimization algorithm Seawater greenhouse Water production

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The alternating direction method of multipliers for finding the distance between ellipsoids

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APPLIED MATHEMATICS AND COMPUTATION 2021年 409卷 126387-126387页

作者： Dolgopolik, Maksim, V Russian Acad Sci Inst Problems Mech Engn VO Bolshoj Pr 61 St Petersburg 199178 Russia

We study several versions of the alternating direction method of multipliers (ADMM) for solving the convex problem of finding the distance between two ellipsoids and the non convex problem of finding the distance between the boundaries of two ellipsoids. In the convex case we present the ADMM with and without automatic penalty updates and demonstrate via numerical experiments on problems of various dimensions that our methods significantly outperform all other existing methods for finding the distance between ellipsoids. In the nonconvex case we propose a heuristic rule for updating the penalty parameter and a heuristic restarting procedure (a heuristic choice of a new starting for point for the second run of the algorithm). The restarting procedure was verified numerically with the use of a global method based on KKT optimality conditions. The results of numerical experiments on various test problems showed that this procedure always allows one to find a globally optimal solution in the nonconvex case. Furthermore, the numerical experiments also demonstrated that our version of the ADMM significantly outperforms existing methods for finding the distance between the boundaries of ellipsoids on problems of moderate and high dimensions.& nbsp;(c) 2021 Elsevier Inc. All rights reserved.

关键词： ADMM Ellipsoid Distance optimization algorithm Nonconvex optimization

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Computer Vision for Small UAS Onboard Pedestrian Detection

Computer Vision for Small UAS Onboard Pedestrian Detection

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AIAA Aviation Forum

作者： Yang, Xuxi Brittaint, Marc Wei, Peng Murphy, Michael Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA AirMap Santa Monica CA 90401 USA

ISBN: (数字)9781624105982

ISBN: (纸本)9781624105982

Computer vision is a key component for safe autonomous flying of small UAS. For example, in a package delivery mission, or an emergency landing event, pedestrian detection could help small UASs with safe landing zone identification. In this research, we focus on deep-learning-based computer vision on a small UAS for pedestrian detection and tracking. In contrast with existing research with ground-level pedestrian detection, our contribution is that we achieve highly accurate multiple pedestrian detection from a birds-eye view, when both the pedestrians and the UAS platform are moving.

关键词： Computer Vision Convolutional Neural Network Emergency Landing Landing Zone Aspect Ratio Unmanned Aerial Vehicle Computing Power Pilot optimization algorithm Separation Assurance

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Aerodynamic Efficiency Analysis of Morphing Wings Relative to Non-Morphing Wings

Aerodynamic Efficiency Analysis of Morphing Wings Relative t...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Montgomery, Zachary S. Hunsaker, Douglas F. Joo, James J. Utah State Univ Mech & Aerosp Engn 4130 Old Main Hill Logan UT 84322 USA US Air Force AFRL RQVS Res Lab 2790 D St Wright Patterson AFB OH 45433 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Advancing materials and manufacturing technologies have progressed allowing the construction of morphing wings that are able to continuously vary certain airfoil parameters such as twist, camber, or control surface deflection as a function of span. A twist effectiveness parameter is presented as a means of comparing different control mechanisms, along with a numerical algorithm capable of calculating the twist effectiveness. A comparison of the efficiency capabilities of continuous (morphing-wing) control surfaces versus discrete (standard-wing) control surfaces is presented for both induced and total drag cases for a wide range of wing planform shapes and control mechanisms. Comparisons of parabolic shaped conformal trailing-edge flaps versus articulated trailing-edge flaps are also presented. Results included here show that using continuous control surfaces instead of discrete control surfaces reduces drag by less than 5% for most applications.

关键词： Flap Deflection Aerodynamic Efficiency High Aspect Ratio Control Surfaces Discrete Control Airfoil Databases Trailing Edge Flap optimization algorithm Airfoil Geometry Zero Lift Drag Coefficient

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