Risk Assessment of Infrastructure Using a Modified Adaptive Neurofuzzy System: Theoretical Application to Sewer Mains-Reference-Cited by-同舟云学术

Risk Assessment of Infrastructure Using a Modified Adaptive Neurofuzzy System: Theoretical Application to Sewer Mains

Published:2024-05 Issue:2 Volume:15 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Abuhishmeh Khaled¹^ORCID,Hojat Jalali Himan²

Affiliation:

1. Ph.D. Candidate, Dept. of Civil Engineering, Univ. of Texas at Arlington, Arlington, TX 76019. ORCID: .

2. Assistant Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, Arlington, TX 76019 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JPSEA2.PSENG-1560

Reference57 articles.

1. Adaptation of Fuzzy Inference System Using Neural Learning

2. Reliability Assessment of Reinforced Concrete Sewer Pipes under Adverse Environmental Conditions: Case Study for the City of Arlington, Texas

3. Abuhishmeh K. S. 2019. “Service life prediction and risk analysis of reinforced concrete gravity flow pipes using reliability theory.” Master’s thesis Dept. of Civil Engineering Univ. of Texas at Arlington.

4. New Multiobjective Optimization Approach to Rehabilitate and Maintain Sewer Networks Based on Whole Lifecycle Behavior

5. Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks

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