Intelligent control for modelling of real‐time reservoir operation

This paper presents a new approach to improving real‐time reservoir operation. The approach combines two major procedures: the genetic algorithm (GA) and the adaptive network‐based fuzzy inference system (ANFIS). The GA is used to search the optimal reservoir operating histogram based on a given inflow series, which can be recognized as the base of input–output training patterns in the next step. The ANFIS is then built to create the fuzzy inference system, to construct the suitable structure and parameters, and to estimate the optimal water release according to the reservoir depth and inflow situation. The practicability and effectiveness of the approach proposed is tested on the operation of the Shihmen reservoir in Taiwan. The current M‐5 operating rule curves of the Shihmen reservoir are also evaluated. The simulation results demonstrate that this new approach, in comparison with the M‐5 rule curves, has superior performance with regard to the prediction of total water deficit and generalized shortage index (GSI). Copyright © 2001 John Wiley & Sons, Ltd.     

A New Echeloned Poisson Series Processor (EPSP)

A specialized Echeloned Poisson Series Processor (EPSP) is proposed. It is a typical software for the implementation of analytical algorithms of Celestial Mechanics. EPSP is designed for manipulating long polynomial-trigonometric series with literal divisors. The coefficients of these echeloned series are the rational or floating-point numbers. The Keplerian processor and analytical generator of special celestial mechanics functions based on the EPSP are also developed.     

BOOK REVIEWS

Book Reviewed in this article: Geographical Aspects of Health and Disease in India . Rais Akhtar and A.T.A. Learmonth , eds . Antarctic Treaty System: An Assessment . Proceedings of a Workshop at Beardmore South Field Camp, Antarctica. American Electoral Mosaics . J. Clark Archer and Fred M. Shelley . Kompas op Suidwes-Afrika/Namibie . W.S. Barnard , ed . Jerusalem in the 19th Century: The Old City . Yehoshua Ben -Arieh . The World as a Total System . Kenneth E. Boulding . A Social History of Housing 1815–1985, Second Ed . John Burnett . Human Migration . W.A.V. Clark . Regional Population Projection Models . Andrei Rogers . The State of Population Theory: Forward from Malthus . David Coleman and Roger Schofield , eds . Imagining Tomorrow: History, Technology and the American Future . Joseph C. Corn , ed. Swidden Agriculture in Indonesia: The Subsistence Strategies of the Kalimantan Kantú . Michael R. Dove . Glacial Geologic Processes . David Drewry . Physics of Desertification . Farouk El -Baz and M.H.A. Hassan , eds . Housing the Homeless . Jon Erickson and Charles Wilhelm , eds . Settlement Patterns in Missouri: A Study of Population Origins, with a Wall Map . Russel L. Gerlach . Desert Development: Man and Technology in Sparselands . Yehuda Gradus , ed . Nuclear Winter. The Evidence and Risks . Owen Greene , Ian Percival and Irene Ridge . The Take-off of Suburbia and the Crisis of the Central City . Günter Heinritz and Elisabeth Lichtenberger , eds . Regional Input-Output Analysis . Geoffrey J. D. Hewings . Spatial Transportation Modeling . Christian Werner . The Atlas of Georgia . Thomas W. Hodler and Howard A. Schretter , eds . Latin America. 5th ed . Preston E. James and C.W. Minkel . Applied Remote Sensing . C.P. Lo . Localities, Class, and Gender . The Lancaster Regionalism Group . Urban Social Movements: The City after Castells . Stuart Lowe . Politics and Method . Doreen Massey and Richard Meegan , eds . Land Use . A. S. Mather . The Kingdom of Coal . Donald L. Miller and Richard E. Sharpless . The Presidio and Militia on the Northern Frontier of New Spain, A Documentary History, Vol. 1: 1570–1700 . Thomas H. Naylor and Charles W. Polzer , S.J., comps . and eds . Nuclear Power: Siting and Safety . Stan Openshaw . The Central African Republic: The Continent's Hidden Heart . Thomas O'Toole . Environmental and Dynamic Geomorphology . Márton Pécsi , ed . Remote Sensing Principles and Interpretation . Floyd F. Sabins , Jr . Acid Rain and Friendly Neighbors: The Policy Dispute between Canada and the United States . Jurgen Schmandt and Hilliard Roderick , eds . Earth's Changing Surface: An Introduction to Geomorphology . M.J. Selby . International Migration: The Female Experience . Rita J. Simon and Caroline B. Brettell , eds . On Geography and Its History . D.R. Stoddart . Transportation Networks: A Quantitative Approach . D. Teodorovic . Processes in Physical Geography . R.D. Thompson , A.M. Mannion , C.W. Mitchell , M. Parry , J.R.G. Townshend . Imaging Radar for Resources Surveys . J.W. Trevett . Dominance and Affection: The Making of Pets . Yi -Fu Tuan . Capturing the Horizon. The Historical Geography of Transportation since the Transportation Revolution of the Sixteenth Century . James E. Vance , Jr . Nations at Risk: The Impact of the Computer Revolution . Edward Yourdon .     

车辆导航系统实现中的关键技术

主要介绍了一个基于PDA的在Windows CE上实现的嵌入式GIS,它可以实时的为移动对象提供基于地理空间位置的综合信息服务。首先介绍了车载导航系统中系统数据的组织方式,主要涉及到数据模型和数据压缩;然后讲述了几种常用的嵌入式操作系统:VxWorks、Windows CE和Linux,由于嵌入式Linux开发难度较大,VxWorks比较昂贵,本系统采用Windows CE作为嵌入式操作系统;最后讲述了系统实现中的关键技术,包括提高地图显示和刷新速度的几种处理技术和系统中采用的地图匹配算法。     

地图合并的技术研究

本文探讨了地图合并技术的研究内容、研究范畴、一般流程;讨论了地图合并的概念、方法;论述了地图合并的主要内容;重点综述了地图合并的相关算法.这些问题的研究丰富完善了地图合并技术的基本理论体系.     

A computational scaling analysis of multiobjective evolutionary algorithms in long-term groundwater monitoring applications

This study contributes a detailed assessment of how increasing problem sizes (measured in terms of the number of decision variables being considered) impacts the computational complexity of using multiple objective evolutionary algorithms (MOEAs) to solve long-term groundwater monitoring (LTM) applications. The epsilon-dominance non-dominated sorted genetic algorithm II (ε-NSGAII), which has been shown to be an efficient and reliable MOEA, was chosen for the computational scaling study. Four design objectives were chosen for the analysis: (i) sampling cost, (ii) contaminant concentration estimation error, (iii) local uncertainty, and (iv) contaminant mass estimation error. The true Pareto-optimal solution set was generated for 18–25 well LTM test cases in order to provide for rigorous algorithm performance assessment for problems of increasing size. Results of the study indicate that the ε-NSGAII exhibits quadratic computational scaling with increasing LTM problem size. However, if the user is willing to accept an approximation to the Pareto-optimal solution set, ε-dominance can be used to reduce the computational scaling of MOEAs to be linear with increasing problem sizes. This study provides a basis for advancing the size and scope of water resources problems that can be effectively solved using MOEAs.     

A diversified multiobjective GA for optimizing reservoir rule curves

The paper develops an efficient macro-evolutionary multiobjective genetic algorithm (MMGA) for optimizing the rule curves of a multi-purpose reservoir system in Taiwan. Macro-evolution is a new kind of high-level species evolution that can avoid premature convergence that may arise during the selection process of conventional GAs. MMGA enriches the capabilities of GA to handle multiobjective problems by diversifying the solution set. Simulation results using a benchmark test problem indicate that the proposed MMGA yields better-spread solutions and converges closer to the true Pareto frontier than the nondominated sorting genetic algorithm-II (NSGA-II). When applied to a real case study, MMGA is able to generate uniformly spread solutions for a two-objective problem involving water supply and hydropower generation. Results of this work indicate that the proposed MMGA is highly competitive and provides a viable alternative to solve multiobjective optimization problems for water resources planning and management.     

Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia

The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.     

Enhanced multi-objective optimization algorithm for renewable energy sources: optimal spatial development of wind farms

A new approach for treating multi-objective spatial optimization problems is introduced in this study, aiming at deriving the optimal spatial allocation of Wind Farms on a Greek Island (Lesvos). This work builds on the knowledge gained from numerous applications of multi-objective genetic algorithms, either for spatial planning purposes or for other engineering-related topics, by incorporating modified genetic operators and sophisticated planning criteria. Hence, a stand-alone genetic optimizer was developed that incorporates the controlled non-dominated sorting genetic algorithm-II (CNSGA-II), in which the user can model all planning criteria and constraints for every spatial entity to be allocated, and handle the genetic solver via a built-in computational framework that permits the analysis of large terrains. The presented paradigm provides interesting findings for the optimal development of renewable energy sources projects whose spatial allocation is governed by conflicting criteria and strict constraints.