Soft Computing Techniques in combating the complexity of the atmosphere- a review
暂无分享,去创建一个
[1] Harry W. Henderson,et al. Obtaining Attractor Dimensions from Meteorological Time Series , 1988 .
[2] Fumiaki Fujibe,et al. Short-term Precipitation Patterns in Central Honshu, Japan Classification with the Fuzzy c-means Met , 1989 .
[3] Konstantine P. Georgakakos,et al. Evidence of Deterministic Chaos in the Pulse of Storm Rainfall. , 1990 .
[4] Jose C. Principe,et al. Prediction of Chaotic Time Series with Neural Networks , 1992 .
[5] D. McCann. A Neural Network Short-Term Forecast of Significant Thunderstorms , 1992 .
[6] Hugh M. Cartwright,et al. Analysis of the distribution of airborne pollution using genetic algorithms , 1993 .
[7] R. A. Scofield,et al. Artificial neural network techniques for estimating heavy convective rainfall and recognizing cloud mergers from satellite data , 1994 .
[8] Lucien Duckstein,et al. Fuzzy rule-based classification of atmospheric circulation patterns , 1995 .
[9] Geza Pesti,et al. A fuzzy rule-based approach to drought assessment , 1996 .
[10] David W. Aha,et al. Improvement to a Neural Network Cloud Classifier , 1996 .
[11] Lucien Duckstein,et al. Relationship Between Monthly Atmospheric Circulation Patterns and Precipitation: Fuzzy Logic and Regression Approaches , 1996 .
[12] Huien Han,et al. Estimation of daily soil water evaporation using an artificial neural network , 1997 .
[13] R. Welch,et al. Automated Cloud Classification of Global AVHRR Data Using a Fuzzy Logic Approach , 1997 .
[14] M. W Gardner,et al. Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences , 1998 .
[15] Shie-Yui Liong,et al. EVIDENCE OF CHAOTIC BEHAVIOR IN SINGAPORE RAINFALL 1 , 1998 .
[16] T. O. Halawani,et al. A neural networks approach for wind speed prediction , 1998 .
[17] A. Mulligan,et al. Genetic Algorithms for Calibrating Water Quality Models , 1998 .
[18] Nikola Kasabov,et al. Integration of connectionist methods and chaotic time‐series analysis for the prediction of process data , 1998 .
[19] William W. Hsieh,et al. Applying Neural Network Models to Prediction and Data Analysis in Meteorology and Oceanography. , 1998 .
[20] Alexander V. Ryzhkov,et al. Cloud Microphysics Retrieval Using S-Band Dual-Polarization Radar Measurements , 1999 .
[21] Jorge Reyes,et al. Prediction of PM2.5 concentrations several hours in advance using neural networks in Santiago, Chile , 2000 .
[22] R. W. McClendon,et al. Estimating daily pan evaporation with artificial neural networks , 2000 .
[23] Valliappa Lakshmanan,et al. Using a Genetic Algorithm to Tune a Bounded Weak Echo Region Detection Algorithm , 2000 .
[24] Bellie Sivakumar,et al. Chaos theory in hydrology: important issues and interpretations , 2000 .
[25] V. Chandrasekar,et al. Classification of Hydrometeors Based on Polarimetric Radar Measurements: Development of Fuzzy Logic and Neuro-Fuzzy Systems, and In Situ Verification , 2000 .
[26] J. Shao,et al. Fuzzy Categorization of Weather Conditions for Thermal Mapping , 2000 .
[27] Jorge Reyes,et al. Prediction of Particlulate Air Pollution using Neural Techniques , 2001, Neural Computing & Applications.
[28] Zekai Sen,et al. Genetic algorithms for the classification and prediction of precipitation occurrence , 2001 .
[29] Laura Bianco,et al. Convective Boundary Layer Depth: Improved Measurement by Doppler Radar Wind Profiler Using Fuzzy Logic Methods , 2002 .
[30] Vicent Gómez,et al. Fuzzy logic and meteorological variables: a case study of solar irradiance , 2002, Fuzzy Sets Syst..
[31] Ajith Abraham,et al. Neurocomputing based Canadian weather analysis , 2002 .
[32] N. D. Kaushika,et al. A Model for the Estimation of Global Solar Radiation Using Fuzzy Random Variables , 2002 .
[33] C. M. Kishtawal,et al. Forecasting summer rainfall over India using genetic algorithm , 2003 .
[34] Archontoula Chaloulakou,et al. Neural Network and Multiple Regression Models for PM10 Prediction in Athens: A Comparative Assessment , 2003, Journal of the Air & Waste Management Association.
[35] Rajib Kumar Bhattacharjya,et al. Optimal design of unit hydrographs using probability distribution and genetic algorithms , 2004 .
[36] Ka Yan Wong,et al. Efficient and Effective Tropical Cyclone Eye Fix Using Genetic Algorithms , 2004, KES.
[37] C. M. Kishtawal,et al. Automatic estimation of tropical cyclone intensity using multi‐channel TMI data: A genetic algorithm approach , 2005 .
[38] J. Hooyberghs,et al. A neural network forecast for daily average PM10 concentrations in Belgium , 2005 .