Prediction of Influent Flow Rate: Data-Mining Approach-Reference-Cited by-同舟云学术

Prediction of Influent Flow Rate: Data-Mining Approach

Published:2013-06 Issue:2 Volume:139 Page:118-123
ISSN:0733-9402
Container-title:Journal of Energy Engineering
language:en
Short-container-title:J. Energy Eng.

Author:

Wei Xiupeng¹,Kusiak Andrew²,Sadat Hosseini Rahil³

Affiliation:

1. Ph.D. Student, Dept. of Mechanical and Industrial Engineering, 3131 Seamans Center, Univ. of Iowa, Iowa City, IA 52242.

2. Professor and Chair, Dept. of Mechanical and Industrial Engineering, 3131 Seamans Center, Univ. of Iowa, Iowa City, IA 52242 (corresponding author).

3. M.S. Student, Dept. of Mechanical and Industrial Engineering, 3131 Seamans Center, Univ. of Iowa, Iowa City, IA 52242.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EY.1943-7897.0000103

Reference34 articles.

1. Data-mining-based methodology for the design of product families

2. Rainfall Estimation by the WSR-88D for Heavy Rainfall Events

3. Intelligent optimal control with dynamic neural networks

4. Prediction of hydraulic load for urban storm control of a municipal WWT plant

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