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Integrating logistic regression with ant colony optimization for smart urban growth modelling

Frontiers of Earth Science 2020年第1期14卷 77-89页

作者： Shifa MA Feng LIU Chunlei MA Xuemin OUYANG School of Architecture and Urban Planning Guangdong University of TechnologyGuangzhou 510090China Shenzhen Longhua District Development Research Institute Shenzhen 518110China School of Marine Sciences Sun Yat-Sen UniversityGuangzhou 510275China

Urban growth does not always strictly follow historical trends;the government may reshape urban growth patterns with considerations of ecological conservation or other plans.Both urban dynamic rules and landscape characteristics are the two main factors influencing the spatial patterns of cities,and obtaining an optimized spatial pattern is veiy important for sustainable urban growth.Therefore,in this study,we integrated logistic regression(LR)with the ant colony optimization(ACO)model to analyze the optimal scenario for smart urban growth.The LR model was used to discuss the relationship between urban patterns and environmental variables such as topography,development centers,and traffic conditions.Then,the urban growth probability was generated using the parameters obtained from LR.The ACO model was further integrated to optimize urban land allocation,which can meet the requirement of high growth probability,and a connected and compacted landscape pattern.This can solve the problem of urban land only being allocated by LR from being distributed fragmentarily in the space.With this integrated model,Guangzhou City,a rapidly developing area in China,was selected as a case study.The urban patterns derived from LR,as well as a simulation scenario using logistic regression-based cellular automata(LR-CA),were used in the comparison.Six landscape metrics were chosen to validate the performance of this proposed model at the pattern level.The results show that the LR-ACO model has a better performance in urban land allocation.This study demonstrated that models that couple dynamic rules and planning objectives can provide plausible scenarios for smart urban growth planning.

关键词： logistic regression ant colony optimization smart growth urban planning

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Investigation on the Anisotropic Transformation Surfaces of Super-Elastic NiTi Shape Memory Alloys Under Multiaxial Cyclic Loading Conditions

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Acta Mechanica Solida Sinica 2018年第6期31卷 744-757页

作者： Bo Qiu Qianhua Kan Tianxing Zhao Xi Xie Guozheng Kang State Key Laboratory of Traction Power Southwest Jiaotong UniversityChengdu 610031China Applied Mechanics and Structure Safety Key Laboratory of Sichuan Province School of Mechanics and EngineeringSouthwest Jiaotong UniversityChengdu 610031China

The cyclic transformation behaviors of polycrystalline super-elastic NiTi shape memory alloys (SMAs)under multiaxial loading paths with different angles between axial and torsional loading orientations were experimentally investigated.The experimental results showed that the start stresses of forward and reverse transformations decreased with the increase'in the number of cycles and exhibit obvious anisotropic evolutions.The start stresses of forward and reverse transformations in the tensile and torsional directions did not satisfy the yon Mises criterion.The shape of transformation surface during the forward and reverse transformations evolved with the increase in the number of cycles.Then,new cyclic anisotropic transformation surfaces were established by introducing an anisotropic tensor into the von Mises equivalent stress based on a typical transformation criterion related to J2 and J3.Moreover,the evolution equations of material parameters used in the proposed transformation surfaces were established to describe the subsequent evolutions of transformation surfaces.Finally,the start stresses of forward and reverse transformations predicted using the proposed transformation surfaces were compared with the experimental results.It shows that the proposed transformation surfaces can reasonably describe the start stresses of forward and reverse transformations,which are helpful for establishing a three-dimensional cyclic constitutive model to describe the cyclic transformation behaviors of super-elastic NiTi SMAs.

关键词： Shape memory alloy Anisotropic response Transformation surface Stress invari- ant Multiaxial cyclic loading

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Design optimization of multilayer perceptron neural network by ant colony optimization applied to engine emissions data

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Science China(Technological Sciences) 2019年第6期62卷 1055-1064页

作者： MARTINEZ-MORALES Jose QUEJ-COSGAYA Hector LAGUNAS-JIMENEZ Jose PALACIOS-HERNANDEZ Elvia MORALES-SALDANA Jorge Faculty of Engineering Autonomous University of Campeche Campeche 24039 Mexico Faculty of Sciences Autonomous University of San Luis Potosi San Luis Potosi 78290 Mexico Faculty of Engineering Autonomous University of San Luis Potosi San Luis Potosi 78290 Mexico

A multilayer perceptron(MLP) artificial neural network(ANN) model has been optimized by the multi-objective ant colony optimization(MOACO) algorithm, which uses three objective functions. A sensitivity analysis to choose MOACO parameter values is carried out by calculating hypervolume metric, and the proposed approach adopts the Vlsekriterijumska Optimizacija I Kompromisno Resenje(VIKOR) decision method to choose final compromised solution on the Pareto front obtained from MOACO. As a result, we used the MLP-MOACO developed model to estimate the value of engine emissions of NOxin a four stroke, spark ignition(SI) gasoline engine and observed acceptable correlation coefficient(R^2) of 0.99978.

关键词： ant colony optimization multilayer perceptron artificial neural networks hypervolume engine emissions

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Model of Underground ant Nest Structure Using Static and Dynamic Finite Element Analysis

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Acta Mechanica Solida Sinica 2018年第6期31卷 717-730页

作者： Wenjun Qu Wei Zhou Peng Zhu Zhi Zhang Department of Structural Engineering Tongji University Shanghai 200092 China The High School Affiliated with Shanghai University Shanghai 200444 Chinch

This paper focuses on the structural characteristics of ant nests,which are complex structures.Natural underground ant nests generally have good air circulation,pressure resistance, waterproof properties,thermal insulation and a favorable temperature and relative humidity. Additionally,ant nests are often surrounded by trees and other natural barriers.In this study, the natural underground ant nests of Iridomyrmex anceps were gathered from different collection sites.Manual cutting and frozen computer numerical control milling were performed on the ant nests in a laboratory.The internal structure of each nest was measured and recorded,and then, the 2D and 3D numerical structure models of the Iridomyrmex anceps nest were created.The static and dynamic simulation analysis of an underground ant nest structure was performed by using finite element analysis software (ABAQUS),and the mechanical properties of the ant nest were discussed.The underground ant nest structure effectively resisted the additional stress due to external static and live loads,and the ant nest was not completely destroyed.

关键词： Underground ant nest Iridomyrmex anceps Frozen CNC milling Finite element analysis Static simulation Dynamic simulation

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ant System Algorithm Research and Its Applications

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High Technology Letters 2002年第4期8卷 91-96页

作者：汪镭 Wu Qidi Qiao Fei Information and Control Dept. of Tongji University Shanghai 200092 P.R.China

In this paper, systematic review on ant System (AS) algorithm research and application is made, and the authors works of introducing As algorithm into continuous space application are summarized. Then the applicabil... 详细信息

关键词： ant system algorithm, continuous space optimization

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Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

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Journal of Modern Power Systems and Clean Energy 2018年第6期6卷 1181-1192页

作者： Ramu SRIKAKULAPU Vinatha U Department of Electrical and Electronics Engineering National Institute of Technology Karnataka

A layout of the offshore wind farm(OSWF)plays a vital role in its capital cost of installation. One of the major contributions in the installation cost is electrical collector system(ECS). ECS includes: submarine cables,number of wind turbines(WTs), offshore platforms etc. By considering the above mentioned problem having an optimized design of OSWF provides the better feasibility in terms of economic considerations. This paper explains the methodology for optimized designing of ECS. The proposed methodology is based on combined elitist ant colony optimization and multiple travelling salesman problem.The objective is to minimize the length of submarine cable connected between WTs and to minimize the wake loss in the wind farm in order to reduce the cost of cable and cable power loss. The methodology is applied on North Hoyle and Horns Rev OSWFs connected with 30 and 80 WTs respectively and the results are presented.

关键词： ant colony optimization Offshore wind farm Multiple travelling salesman problem Wake effect Wake loss

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ant Colony Optimization for Feature Selection in Software Product Lines

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Journal of Shanghai Jiaotong university(Science) 2014年第1期19卷 50-58页

作者：王英林庞金伟 School of Information Management and Engineering Shanghai University of Finance and Economics Department of Computer Science and Engineering Shanghai Jiaotong University

Software product lines(SPLs) are important software engineering techniques for creating a collection of similar software systems. Software products can be derived from SPLs quickly. The process of software product derivation can be modeled as feature selection optimization with resource constraints, which is a nondeterministic polynomial-time hard(NP-hard) problem. In this paper, we present an approach that using ant colony optimization to get an approximation solution of the problem in polynomial time. We evaluate our approach by comparing it to two important approximation techniques. One is filtered Cartesian flattening and modified heuristic(FCF+M-HEU) algorithm, the other is genetic algorithm for optimized feature selection(GAFES). The experimental results show that our approach performs 6% worse than FCF+M-HEU with reducing much running time. Meanwhile, it performs 10% better than GAFES with taking more time.

关键词： ant colony optimization ant colony system software product lines feature model

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Impact of the red imported fire ant Solenopsis invicta Buren on biodiversity in South China: A review

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Journal of Integrative Agriculture 2019年第4期18卷 788-796页

作者： WANG Lei XU Yi-juan ZENG Ling LU Yong-yue Red Imported Fire ant Research Centre South China Agricultural University

The red imported fire ant, Solenopsis invicta, is a problematic invasive species in China since at least 2003. Over the past 15 years, a numerous studies were published on the impacts of this species on flora, fauna, and ecosystem function in natural and agricultural systems. We reviewed the literature on S. invicta invasion biology and impacts on biodiversity in South China. Both monogyne and polygyne colonies of S. invicta were introduced to China and polygyne colony is the dominant type. The range expansion rate of S. invicta may reach 26.5–48.1 km yr–1 in China. S. invicta forage activities occur year-round, peaking in the summer and fall in South China and show a preference for insects and plant seeds. We describe the ecological impacts of S. invicta on various habitats in South China, including arthropod community structure disruption and decreases in diversity and abundance of native ant species. S. invicta can replace the role of native ants in mutualisms between ants and honeydew-producing Hemiptera, which results in loss of important food resources for native ants and natural enemies of hemipterans. Further research is required to assess the complex ecosystem-level impacts of S. invicta in introduced areas.

关键词： fire ant biology behavior ecosystem function non-native invasion

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Smart Semi-active PID-ACO control strategy for tower vibration reduction in Wind Turbines with MR damper

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Earthquake Engineering and Engineering Vibration 2019年第4期18卷 887-902页

作者： Mahmudur Rahman Zhi Chao Ong Wen Tong Chong Sabariah Julai Department of Mechanical Engineering Faculty of Engineering University of Malaya

Wind turbine technology is well known around the globe as an eco-friendly and eff ective renewable power source. However, this technology often faces reliability problems due to structural vibration. This study proposes a smart semi-active vibration control system using Magnetorheological (MR) dampers where feedback controllers are optimized with nature-inspired algorithms. Proportional integral derivative (PID) and Proportional integral (PI) controllers are designed to achieve the optimal desired force and current input for MR the damper. PID control parameters are optimized using an ant colony optimization (ACO) algorithm. The eff ectiveness of the ACO algorithm is validated by comparing its performance with Ziegler-Nichols (Z-N) and particle swarm optimization (PSO). The placement of the MR damper on the tower is also investigated to ensure structural balance and optimal desired force from the MR damper. The simulation results show that the proposed semi-active PID-ACO control strategy can signifi cantly reduce vibration on the wind turbine tower under diff erent frequencies (i.e., 67%, 73%, 79% and 34.4% at 2 Hz, 3 Hz, 4.6 Hz and 6 Hz, respectively) and amplitudes (i.e. 50%, 58% and 67% for 50 N, 80 N, and 100 N, respectively). In this study, the simulation model is validated with an experimental study in terms of natural frequency, mode shape and uncontrolled response at the 1st mode. The proposed PID-ACO control strategy and optimal MR damper position is also implemented on a lab-scaled wind turbine tower model. The results show that the vibration reduction rate is 66% and 73% in the experimental and simulation study, respectively, at the 1st mode.

关键词： ant colony optimization fi nite diff erence method magnetorheological damper PID-ACO controller semiactive control system identifi cation wind turbine tower

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Churn-Resilient Task Scheduling in a Tiered IoT Infrastructure

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China Communications 2019年第8期16卷 162-175页

作者： Jianhua Fan Xianglin Wei Tongxiang Wang Tian Lan Suresh Subramaniam Nanjing Telecommunication Technology Research Institute Nanjing210007China George Washington University Washington DC20052US

Cloud-as-the-center computing paradigms face multiple challenges in the 5G and Internet of Things scenarios, where the service requests are usually initiated by the end-user devices located at network edge and have rigid time constraints. Therefore, Fog computing, or mobile edge computing, is introduced as a promising solution to the service provision in the tiered IoT infrastructure to compensate the shortage of traditional cloud-only architecture. In this cloud-to-things continuum, several cloudlet or mobile edge server entities are placed at the access network to handle the task offloading and processing problems at the network edge. This raises the resource scheduling problem in this tiered system, which is vital for the promotion of the system efficiency. Therefore, in this paper, a scheduling mechanism for the cloudlets or fog nodes are presented, which takes the mobile tasks’ deadline and resources requirements at the same time while promoting the overall profit of the system. First, the problem at the cloudlet, to which IoT devices offload their tasks, is formulated as a multi-dimensional 0-1 knapsack problem. Second, based on ant colony optimization, a scheduling algorithm is presented which treat this problem as a subset selection problem. Third, to promote the performance of the system in the dynamic environments,a churn-refined algorithm is further put forward. A series of simulation experiments have shown that out proposal outperforms many state-of-the-art algorithms in both profit and guarantee ratio.

关键词： fog computing task scheduling deadline constrained internet of things ant colony optimization

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