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Table of Contents
Acknowledgments; Contents; 1 Introduction; Abstract; 1.1 Introduction; References; 2 Selection of Water Quality Monitoring Stations; Abstract; 2.1 Historical Background; 2.2 Sanders Method; 2.3 Multiple-Criteria Decision Making (MCDM) Method; 2.3.1 Making Dimensionless; 2.3.2 Assessment of Weighting (Wj) for Attributes; 2.4 Dynamic Programming Approach (DPA) Method; 2.4.1 The DPA Theory; 2.4.2 Normalization and Uniformization Procedure; 2.5 Application of Sanders Method; 2.5.1 Comment on the Application; References; 3 Water Quality Indices (WQI); Abstract; 3.1 Historical Background
3.2 Summary of WQI Methods3.3 National Sanitation Foundation's Water Quality Index (NSFWQI) Method; 3.4 British Colombia Water Quality Index as (BCWQI) Method; 3.5 Application of NFSWQI Method, a Case Study: K0101r016Bn River (Iran); 3.6 Application of NSFWQI Method in Sefid-Rud River (Iran); 3.7 Application of BCWQI Method in Sefid-Rud River (Iran); 3.8 Comments on Application; References; 4 Time Series Modeling; Abstract; 4.1 Introduction; 4.2 Historical Background; 4.3 Time Series; 4.4 Forecast Error; 4.5 Box-Jenkins Methodology for Time Series Modeling
4.6 Stationary and Non-stationary Time Series4.7 The Sample Autocorrelation and Partial Autocorrelation Functions; 4.8 Classification of Non-seasonal Time Series Models; 4.9 Guidelines for Choosing a Non-seasonal Models; 4.10 Seasonal Box-Jenkins Models; 4.11 Guidelines for Identification of Seasonal Models; 4.12 Diagnostic Checking; 4.13 Exponential Smoothing Methods; 4.13.1 Simple Exponential Smoothing; 4.14 Winter's Method; 4.15 One and Two-Parameter Double Exponential Smoothing; 4.16 Adaptive Control Procedures; 4.17 Application of Time Series
4.17.1 A Case Study: Latian Dam Water Quality4.17.1.1 The Software; 4.17.1.2 Selected Models of Few Water Quality Parameters in Zir-e-Pol Station; Ca++; SO4&hx2013; &hx2013; ; Acidity (pH); Total Dissolved Solid (TDS); 4.18 Summary; References; 5 Artificial Neural Network; Abstract; 5.1 Introduction; 5.2 Historical Background; 5.3 Artificial Neural Network Theory; 5.3.1 Theory of ANN; 5.3.2 Dynamic ANN Models; 5.3.3 Data Preparation; 5.3.4 Learning Rate; 5.3.5 Model Efficiency; 5.4 Application of Artificial Neural Network; 5.4.1 A Case Study: Zaribar Water Quality (Iran); 5.4.1.1 Comment
3.2 Summary of WQI Methods3.3 National Sanitation Foundation's Water Quality Index (NSFWQI) Method; 3.4 British Colombia Water Quality Index as (BCWQI) Method; 3.5 Application of NFSWQI Method, a Case Study: K0101r016Bn River (Iran); 3.6 Application of NSFWQI Method in Sefid-Rud River (Iran); 3.7 Application of BCWQI Method in Sefid-Rud River (Iran); 3.8 Comments on Application; References; 4 Time Series Modeling; Abstract; 4.1 Introduction; 4.2 Historical Background; 4.3 Time Series; 4.4 Forecast Error; 4.5 Box-Jenkins Methodology for Time Series Modeling
4.6 Stationary and Non-stationary Time Series4.7 The Sample Autocorrelation and Partial Autocorrelation Functions; 4.8 Classification of Non-seasonal Time Series Models; 4.9 Guidelines for Choosing a Non-seasonal Models; 4.10 Seasonal Box-Jenkins Models; 4.11 Guidelines for Identification of Seasonal Models; 4.12 Diagnostic Checking; 4.13 Exponential Smoothing Methods; 4.13.1 Simple Exponential Smoothing; 4.14 Winter's Method; 4.15 One and Two-Parameter Double Exponential Smoothing; 4.16 Adaptive Control Procedures; 4.17 Application of Time Series
4.17.1 A Case Study: Latian Dam Water Quality4.17.1.1 The Software; 4.17.1.2 Selected Models of Few Water Quality Parameters in Zir-e-Pol Station; Ca++; SO4&hx2013; &hx2013; ; Acidity (pH); Total Dissolved Solid (TDS); 4.18 Summary; References; 5 Artificial Neural Network; Abstract; 5.1 Introduction; 5.2 Historical Background; 5.3 Artificial Neural Network Theory; 5.3.1 Theory of ANN; 5.3.2 Dynamic ANN Models; 5.3.3 Data Preparation; 5.3.4 Learning Rate; 5.3.5 Model Efficiency; 5.4 Application of Artificial Neural Network; 5.4.1 A Case Study: Zaribar Water Quality (Iran); 5.4.1.1 Comment