Artificial Intelligence techniques: An introduction to their use for modelling environmental systems

Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model environmental systems. We review some of them and their environmental applicability, with examples and a reference list. The techniques covered are case-based reasoning, rule-based systems, artificial neural networks, fuzzy models, genetic algorithms, cellular automata, multi-agent systems, swarm intelligence, reinforcement learning and hybrid systems.

[1]  Aaron C. Zecchin,et al.  Optimising the mutual information of ecological data clusters using evolutionary algorithms , 2006, Math. Comput. Model..

[2]  M. Yong,et al.  Intelligent control aeration and external carbon addition for improving nitrogen removal , 2006, Environ. Model. Softw..

[3]  Janet L. Kolodner,et al.  An introduction to case-based reasoning , 1992, Artificial Intelligence Review.

[4]  Qing Zhang,et al.  Forecasting raw-water quality parameters for the North Saskatchewan River by neural network modeling , 1997 .

[5]  L. P. Khoo,et al.  A Tabu-Enhanced Genetic Algorithm Approach to Agile Manufacturing , 2002 .

[6]  Niandry Moreno,et al.  Biocomplexity of deforestation in the Caparo tropical forest reserve in Venezuela: An integrated multi-agent and cellular automata model , 2007, Environ. Model. Softw..

[7]  J Comas,et al.  Development of a Case-Based System for the Supervision of an Activated Sludge Process , 2001, Environmental technology.

[8]  W. Spataro,et al.  Analysing Lava Risk for the Etnean Area: Simulation by Cellular Automata Methods , 1999 .

[9]  Claudia Pahl-Wostl,et al.  Information, public empowerment, and the management of urban watersheds , 2005, Environ. Model. Softw..

[10]  Claudia Bauzer Medeiros,et al.  Supporting modeling and problem solving from precedent experiences: the role of workflows and case-based reasoning , 2005, Environ. Model. Softw..

[11]  Ignasi Rodríguez-Roda,et al.  Exploring the ecological status of human altered streams through Generative Topographic Mapping , 2007, Environ. Model. Softw..

[12]  Seref Naci Engin,et al.  Determination of the relationship between sewage odour and BOD by neural networks , 2005, Environ. Model. Softw..

[13]  Peng-Yeng Yin,et al.  A particle swarm optimization approach to the nonlinear resource allocation problem , 2006, Appl. Math. Comput..

[14]  Paul W. H. Chung,et al.  Case-Based Reasoning for Estuarine Model Design , 2002, ECCBR.

[15]  B. Henderson-Sellers,et al.  Mathematics and Computers in Simulation , 1995 .

[16]  K.-Peter Holz,et al.  Short-term water level prediction using neural networks and neuro-fuzzy approach , 2003, Neurocomputing.

[17]  Mohammad N. Almasri,et al.  Modular neural networks to predict the nitrate distribution in ground water using the on-ground nitrogen loading and recharge data , 2005, Environ. Model. Softw..

[18]  Miklas Scholz,et al.  Constructed Wetlands: Prediction of Performance with Case-based Reasoning (Part B) , 2006 .

[19]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[20]  Yuanhai Li,et al.  Optimal groundwater monitoring design using an ant colony optimization paradigm , 2007, Environ. Model. Softw..

[21]  Van-Nam Huynh,et al.  A context-dependent knowledge model for evaluation of regional environment , 2005, Environ. Model. Softw..

[22]  Robert Fullér,et al.  Introduction to neuro-fuzzy systems , 1999, Advances in soft computing.

[23]  Frederick E. Petry,et al.  Genetic Algorithms , 1992 .

[24]  Jan-Tai Kuo,et al.  A hybrid neural-genetic algorithm for reservoir water quality management. , 2006, Water research.

[25]  D. Signorini,et al.  Neural networks , 1995, The Lancet.

[26]  Ana P. Barros,et al.  Quantitative flood forecasting using multisensor data and neural networks , 2001 .

[27]  Graciela Metternicht,et al.  FUERO: foundations of a fuzzy exploratory model for soil erosion hazard prediction , 2005, Environ. Model. Softw..

[28]  David W. Roberts,et al.  Modelling forest dynamics with vital attributes and fuzzy systems theory , 1996 .

[29]  Nikolaos M. Avouris,et al.  Short-term air quality prediction using a case-based classifier , 2001, Environ. Model. Softw..

[30]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[31]  David Batten,et al.  Are some human ecosystems self-defeating? , 2007, Environ. Model. Softw..

[32]  François Bousquet,et al.  Multi-agent simulations and ecosystem management: a review , 2004 .

[33]  Carlo Marchini,et al.  A fuzzy logic model to recognise ecological sectors in the lagoon of Venice based on the benthic community , 2006 .

[34]  Kwok-Wing Chau,et al.  A Split-Step PSO Algorithm in Prediction of Water Quality Pollution , 2005, ISNN.

[35]  Ron Janssen,et al.  Decision support for integrated wetland management , 2005, Environ. Model. Softw..

[36]  Ferhat Karaca,et al.  NN-LEAP: A neural network-based model for controlling leachate flow-rate in a municipal solid waste landfill site , 2006, Environ. Model. Softw..

[37]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[38]  Nikolaos F. Matsatsinis,et al.  Intelligent Decision Support Methods , 2003 .

[39]  Lazaros S. Iliadis,et al.  A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation , 2005, Environ. Model. Softw..

[40]  Iain Brown,et al.  Modelling future landscape change on coastal floodplains using a rule-based GIS , 2006, Environ. Model. Softw..

[41]  Keung-Chi Ng,et al.  Uncertainty management in expert systems , 1990, IEEE Expert.

[42]  Toshihiko Takeuchi,et al.  Integrated environmental management process applying genetic algorithm , 1999 .

[43]  I. Bogardi,et al.  Application of fuzzy rule-based modeling technique to regional drought , 1999 .

[44]  J. Molofsky,et al.  A New Kind of Ecology? , 2004 .

[45]  Christophe Le Page,et al.  Agent based simulation of a small catchment water management in northern Thailand: Description of the CATCHSCAPE model , 2003 .

[46]  Andrzej Pekalski,et al.  Dynamics of Populations in Extended Systems , 2002, ACRI.

[47]  Jingyu Wang,et al.  Ant colony optimization for the nonlinear resource allocation problem , 2006, Appl. Math. Comput..

[48]  Domenico Camarda,et al.  Mobility in Environmental Planning: An Integrated Multi-agent Approach , 2005, CDVE.

[49]  Stefania Bandini,et al.  Simulation of Vegetable Populations Dynamics Based on Cellular Automata , 2002, ACRI.

[50]  C. P. Yialouris,et al.  DIARES-IPM: a diagnostic advisory rule-based expert system for integrated pest management in Solanaceous crop systems , 2003 .

[51]  Georgios Dounias,et al.  Hybrid Computational Intelligence in Medicine , 2003 .

[52]  Tahir Husain,et al.  A fuzzy-based methodology for an aggregative environmental risk assessment: a case study of drilling waste , 2005, Environ. Model. Softw..

[53]  James R. Craig,et al.  Pump-and-treat optimization using analytic element method flow models , 2006 .

[54]  E. F. Codd,et al.  Cellular automata , 1968 .

[55]  Nigel Ford Expert systems and artificial intelligence , 1991 .

[56]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[57]  Kwok-wing Chau,et al.  Particle Swarm Optimization Training Algorithm for ANNs in Stage Prediction of Shing Mun River , 2006 .

[58]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[59]  Samira El Yacoubi,et al.  LUCAS: an original tool for landscape modelling , 2003, Environ. Model. Softw..

[60]  Holger R. Maier,et al.  Use of artificial neural networks for modelling cyanobacteria Anabaena spp. in the River Murray, South Australia , 1998 .

[61]  S Forrest,et al.  Genetic algorithms , 1996, CSUR.

[62]  Raymond R. Tan,et al.  Hybrid evolutionary computation for the development of pollution prevention and control strategies , 2007 .

[63]  Ian D. Watson,et al.  An Introduction to Case-Based Reasoning , 1995, UK Workshop on Case-Based Reasoning.

[64]  Peter Droogers,et al.  Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture , 2006 .

[65]  Miquel Sànchez-Marrè,et al.  A comparative study on the use of similarity measures in case-based reasoning to improve the classification of environmental system situations , 2004, Environ. Model. Softw..

[66]  C. V. Negoiţă,et al.  Expert systems and fuzzy systems , 1985 .

[67]  K. N. Dollman,et al.  - 1 , 1743 .

[68]  Dan Boneh,et al.  On genetic algorithms , 1995, COLT '95.

[69]  Isaac Meilijson,et al.  Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior , 2002, Neurocomputing.

[70]  Gerhard Weiss,et al.  Multiagent Systems , 1999 .

[71]  S. El Yacoubi,et al.  Cellular automata modelling and spreadability , 2002 .

[72]  Robert M. Itami,et al.  Simulating spatial dynamics: cellular automata theory , 1994 .

[73]  Chris T. Kiranoudis,et al.  Automatic identification of oil spills on satellite images , 2006, Environ. Model. Softw..

[74]  T. C. Bartee,et al.  Expert systems and artificial intelligence , 1988 .

[75]  Francisco Herrera,et al.  Analysis of the Best-Worst Ant System and Its Variants on the QAP , 2002, Ant Algorithms.

[76]  Alexander B. Sideridis,et al.  A diagnostic expert system for honeybee pests , 2002 .

[77]  Wayne Woldt,et al.  Fuzzy rule-based approach to describe solute transport in the unsaturated zone , 1999 .

[78]  Maja Schlüter,et al.  Application of a GIS-based simulation tool to illustrate implications of uncertainties for water management in the Amudarya river delta , 2007, Environ. Model. Softw..

[79]  Pieter Abbeel,et al.  Using inaccurate models in reinforcement learning , 2006, ICML.

[80]  Anil K. Jain,et al.  Artificial Neural Networks: A Tutorial , 1996, Computer.

[81]  X. Yao Evolving Artificial Neural Networks , 1999 .

[82]  M. Karamouz,et al.  Water allocation improvement in river basin using Adaptive Neural Fuzzy Reinforcement Learning approach , 2007, Appl. Soft Comput..

[83]  Michael Monticino,et al.  Coupled human and natural systems: A multi-agent-based approach , 2007, Environ. Model. Softw..

[84]  Quan J. Wang,et al.  Using genetic algorithms to optimise model parameters , 1997 .

[85]  Herry Purnomo,et al.  Developing multi-stakeholder forest management scenarios: a multi-agent system simulation approach applied in Indonesia , 2005 .

[86]  Miquel Sànchez-Marrè,et al.  Sustainable case learning for continuos domains , 1999, Environ. Model. Softw..

[87]  Frada Burstein,et al.  A case-based fuzzy multicriteria decision support model for tropical cyclone forecasting , 2005, Eur. J. Oper. Res..

[88]  Suzana Dragicevic,et al.  A fuzzy-constrained cellular automata model of forest insect infestations , 2006 .

[89]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[90]  Marco Dorigo,et al.  Ant algorithms and stigmergy , 2000, Future Gener. Comput. Syst..

[91]  Rocco Rongo,et al.  Modelling Surface Flows for Macroscopic Phenomena by Cellular Automata: An Application to Debris Flows , 2002, ACRI.

[92]  D. Hammerstrom,et al.  Working with neural networks , 1993, IEEE Spectrum.

[93]  S. Le Hegarat-Mascle,et al.  Swarm intelligence in optimisation problems , 2003 .

[94]  René Bañares-Alcántara,et al.  Minimising environmental impact using CBR: an azeotropic distillation case study , 1999, Environ. Model. Softw..

[95]  B. Baets,et al.  Fuzzy rule-based macroinvertebrate habitat suitability models for running waters , 2006 .

[96]  Lazaros S. Iliadis,et al.  Time-series modeling of fishery landings using ARIMA models and Fuzzy Expected Intervals software , 2006, Environ. Model. Softw..

[97]  Agostino Poggi,et al.  Multiagent Systems , 2006, Intelligenza Artificiale.

[98]  Richard S. Sutton,et al.  Reinforcement Learning , 1992, Handbook of Machine Learning.

[99]  A. Martín del Rey,et al.  Modelling forest fire spread using hexagonal cellular automata , 2007 .

[100]  Angus R. Simpson,et al.  Ant Colony Optimization for Design of Water Distribution Systems , 2003 .

[101]  Thomas Berger,et al.  Agent-based spatial models applied to agriculture: A simulation tool , 2001 .

[102]  Mance E. Harmon,et al.  Reinforcement Learning: A Tutorial. , 1997 .

[103]  Georgios Ch. Sirakoulis,et al.  A cellular automaton simulation tool for modelling seismicity in the region of Xanthi , 2007, Environ. Model. Softw..

[104]  Michael Sampels,et al.  A MAX-MIN Ant System for the University Course Timetabling Problem , 2002, Ant Algorithms.

[105]  Jan Broeze,et al.  Generalised and instance-specific modelling for biological systems , 1999, Environ. Model. Softw..

[106]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[107]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[108]  Roberto Montemanni,et al.  Time dependent vehicle routing problem with a multi ant colony system , 2008, Eur. J. Oper. Res..

[109]  Barnali M. Dixon,et al.  Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis , 2005 .

[110]  Francesco Ricci,et al.  Interactive Case-Based Planning for Forest Fire Management , 2000, Applied Intelligence.

[111]  Suzana Dragicevic,et al.  iCity: A GIS-CA modelling tool for urban planning and decision making , 2007, Environ. Model. Softw..

[112]  J. Boaventura Cunha,et al.  Greenhouse air temperature predictive control using the particle swarm optimisation algorithm , 2005 .

[113]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[114]  Willi-Hans Steeb,et al.  The Nonlinear Workbook , 2005 .

[115]  Seyed Alireza Seyedin,et al.  Swarm intelligence based classifiers , 2007, J. Frankl. Inst..

[116]  Graeme McFerren,et al.  Fuzzy expert systems and GIS for cholera health risk prediction in southern Africa , 2007, Environ. Model. Softw..

[117]  Mohammad Hadi Afshar,et al.  Improving the efficiency of ant algorithms using adaptive refinement: Application to storm water network design , 2006 .

[118]  Frederick Hayes-Roth,et al.  Rule-based systems , 1985, CACM.

[119]  Stephen Wolfram,et al.  Universality and complexity in cellular automata , 1983 .

[120]  Tanja Tötzer,et al.  Modeling growth and densification processes in sub-urban regions – simulation of landscape transition with spatial agents , 2005 .

[121]  Lael Parrott,et al.  Design considerations for the implementation of multi-agent systems in the dairy industry , 2003 .

[122]  Chuntian Cheng,et al.  Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration , 2002 .

[123]  Angus R. Simpson,et al.  Application of two ant colony optimisation algorithms to water distribution system optimisation , 2006, Math. Comput. Model..

[124]  Nonlinear aspects of data integration for land-cover classification in a neural network environment , 1994 .

[125]  S. I. V. Sousa,et al.  Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations , 2007, Environ. Model. Softw..

[126]  Amit Kumar,et al.  An evaluation of artificial neural network technique for the determination of infiltration model parameters , 2006, Appl. Soft Comput..

[127]  A. Mynett,et al.  Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches , 2006 .

[128]  Miquel Sànchez-Marrè,et al.  Learning and Adaptation in Wastewater Treatment Plants Through Case–Based Reasoning , 1997 .

[129]  A. M. Crowe,et al.  An application of genetic algorithms to the robust estimation of soil organic and mineral fraction densities , 2006, Environ. Model. Softw..

[130]  P. Snow,et al.  Introduction to artificial neural networks for physicians: Taking the lid off the black box , 2001, The Prostate.

[131]  A. Tsoularis,et al.  Reinforcement learning for a stochastic automaton modelling predation in stationary model-mimic environments. , 2005, Mathematical biosciences.

[132]  Giandomenico Spezzano,et al.  A model based on cellular automata for the parallel simulation of 3D unsaturated flow , 2006, Parallel Comput..

[133]  David R. B. Stockwell,et al.  The use of the GARP genetic algorithm and internet grid computing in the Lifemapper world atlas of species biodiversity , 2005, ArXiv.

[134]  Fu Zetian,et al.  Pig-vet: a web-based expert system for pig disease diagnosis , 2005 .

[135]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[136]  C. L. Changa,et al.  Applying fuzzy theory and genetic algorithm to interpolate precipitation , 2005 .

[137]  Michel Dreyfus-León,et al.  Individual-based modelling of fishermen search behaviour with neural networks and reinforcement learning , 1999 .

[138]  M. Janssen,et al.  Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review , 2003 .

[139]  Hikmet Kerem Cigizoglu,et al.  Generalized regression neural network in modelling river sediment yield , 2006, Adv. Eng. Softw..

[140]  Fred Collopy,et al.  How effective are neural networks at forecasting and prediction? A review and evaluation , 1998 .

[141]  S. M. Lo,et al.  Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong , 2003, Neurocomputing.

[142]  Vasant Dhar,et al.  Intelligent Decision Support Methods: The Science of Knowledge Work , 1996 .

[143]  Ahmed A. Rafea,et al.  Pest Control Expert System for Tomato (PCEST) , 2000, Knowledge and Information Systems.

[144]  Nikolaos M. Avouris,et al.  Feature selection for air quality forecasting: a genetic algorithm approach , 2003, AI Commun..

[145]  Farhi Marir,et al.  Case-based reasoning: A review , 1994, The Knowledge Engineering Review.

[146]  Raymond R. Tan,et al.  Rule-based life cycle impact assessment using modified rough set induction methodology , 2005, Environ. Model. Softw..

[147]  Luis A. Bastidas,et al.  Multiobjective particle swarm optimization for parameter estimation in hydrology , 2006 .

[148]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[149]  Gianni Bellocchi,et al.  PTFIndicator: An IRENE_DLL-based application to evaluate estimates from pedotransfer functions by integrated indices , 2006, Environ. Model. Softw..

[150]  Hong Zhang,et al.  Particle swarm optimization for resource-constrained project scheduling , 2006 .

[151]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[152]  Steven C. Chapra,et al.  QUAL2Kw - A framework for modeling water quality in streams and rivers using a genetic algorithm for calibration , 2006, Environ. Model. Softw..

[153]  Karim C. Abbaspour,et al.  Estimating unsaturated soil hydraulic parameters using ant colony optimization , 2001 .

[154]  Samuel H. Huang,et al.  Neural-expert hybrid approach for intelligent manufacturing: a survey , 1995 .

[155]  Miquel Sànchez-Marrè,et al.  OntoWEDSS: augmenting environmental decision-support systems with ontologies , 2004, Environ. Model. Softw..

[156]  Yiheyis Maru,et al.  Australian rangelands as complex adaptive systems: A conceptual model and preliminary results , 2006, Environ. Model. Softw..

[157]  M. Fonstad Cellular automata as analysis and synthesis engines at the geomorphology–ecology interface , 2006 .

[158]  Donald E. Grierson,et al.  Comparison among five evolutionary-based optimization algorithms , 2005, Adv. Eng. Informatics.

[159]  Angus R. Simpson,et al.  Parametric study for an ant algorithm applied to water distribution system optimization , 2005, IEEE Transactions on Evolutionary Computation.

[160]  Axel Bronstert,et al.  1-, 2- and 3-dimensional modeling of water movement in the unsaturated soil matrix using a fuzzy approach , 1995 .

[161]  Lazaros S. Iliadis,et al.  An Artificial Neural Network model for mountainous water-resources management: The case of Cyprus mountainous watersheds , 2007, Environ. Model. Softw..

[162]  Gabriel Ibarra-Berastegi,et al.  Regression and multilayer perceptron-based models to forecast hourly O3 and NO2 levels in the Bilbao area , 2006, Environ. Model. Softw..

[163]  Victor R. Lesser,et al.  Multiagent systems: an emerging subdiscipline of AI , 1995, CSUR.

[164]  Alan Bundy,et al.  Artificial Intelligence Techniques: A Comprehensive Catalogue , 1996 .

[165]  Ashu Jain,et al.  A comparative analysis of training methods for artificial neural network rainfall-runoff models , 2006, Appl. Soft Comput..

[166]  M. Termansen,et al.  The use of genetic algorithms and Bayesian classification to model species distributions , 2006 .

[167]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[168]  Patrick Siarry,et al.  Particle swarm and ant colony algorithms hybridized for improved continuous optimization , 2007, Appl. Math. Comput..

[169]  François Bousquet,et al.  Suitability of Multi-Agent Simulations to study irrigated system viability: application to case studies in the Senegal River Valley , 2004 .

[170]  M. Hare,et al.  Further towards a taxonomy of agent-based simulation models in environmental management , 2004, Math. Comput. Simul..

[171]  Richard F. Hartl,et al.  An improved Ant System algorithm for theVehicle Routing Problem , 1999, Ann. Oper. Res..

[172]  Nicolas Moussiopoulos,et al.  PM10 forecasting for Thessaloniki, Greece , 2006, Environ. Model. Softw..

[173]  Birgitt Schönfisch,et al.  A Fish Migration Model , 2002, ACRI.

[174]  Roberto A. Flores-Mendez Towards a standardization of multi-agent system framework , 1999, CROS.

[175]  Ioannis G. Karafyllidis,et al.  A model for predicting forest fire spreading using cellular automata , 1997 .

[176]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[177]  Asaad Y. Shamseldin,et al.  A non-linear combination of the forecasts of rainfall-runoff models by the first-order Takagi–Sugeno fuzzy system , 2001 .

[178]  R. Shuchman,et al.  Operational algorithm for the retrieval of water quality in the Great Lakes , 2005 .

[179]  Miklas Scholz,et al.  Constructed Wetlands: Treatment of Concentrated Storm Water Runoff (Part A) , 2006 .