Journal of Geoscience and Environment Protection

Journal of Geoscience and Environment Protection

ISSN Print: 2327-4336
ISSN Online: 2327-4344
www.scirp.org/journal/gep
E-mail: gep@scirp.org
"Prediction of Sewer Pipe Main Condition Using the Linear Regression Approach"
written by Ali Gedam, Suraj Mangulkar, Bal Gandhi,
published by Journal of Geoscience and Environment Protection, Vol.4 No.5, 2016
has been cited by the following article(s):
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[9] corrected Proof
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[10] Image processing-based framework for determining of growth in sewer pipe defects
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[11] Risk-based Rehabilitation of Wastewater Pipes
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[12] Operational Risk-Based Decision Making for Wastewater Pipe Management
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[13] Development of a Model to Prioritize Inspection and Condition Assessment of Gravity Sanitary Sewer Systems
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[14] Application of Supervised Machine Learning Algorithms for Developing Service Life Prediction Model of Sewer Pipes
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[15] Factors Influencing the Condition of Sewer Pipes: State-of-the-Art Review
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[16] Geoadditive Quantile Regression Model for Sewer Pipes Deterioration Using Boosting Optimization Algorithm
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[17] Statistical Inference of Sewer Pipe Deterioration Using Bayesian Geoadditive Regression Model
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[18] Number of Blockage Prediction for Sanitary Sewer Networks (Case Study: Isfahan Region 2)
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[19] Predictive Model Development to Perform Condition Assessment on Pipeline Networks
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[20] DEVELOPMENT OF CONDITION PREDICTION MODELS FOR SANITARY SEWER PIPES
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[21] Wastewater Pipe Condition Rating Model Using Multicriteria Decision Analysis
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[22] Automatic Detection and Classification of Sewer Defects via Hierarchical Deep Learning
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[23] پیش‌بینی تعداد گرفتگی در شبکه فاضلاب شهری (مطالعه موردی: منطقه دو اصفهان)‎
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[24] DEVELOPMENT OF CONDITION PREDICTION MODELS
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[25] Wastewater Pipe Condition and Deterioration Modeling for Risk-Based Decision-Making
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[26] Sewer Structural Condition Prediction Integrating Bayesian Model Averaging with Logistic Regression
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