Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning

2004 ◽  
Vol 39 (10) ◽  
pp. 1235-1242 ◽  
Author(s):  
Gwang-Hee Kim ◽  
Sung-Hoon An ◽  
Kyung-In Kang
Keyword(s):  
Neural Networks ◽  
Regression Analysis ◽  
Construction Cost ◽  
Case Based Reasoning ◽  
Cost Estimating ◽  
Case Based

scholarly journals Using extended siamese networks to provide decision support in aquaculture operations

2021 ◽  
Author(s):  
Bjørn Magnus Mathisen ◽  
Kerstin Bach ◽  
Agnar Aamodt
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Similar Case ◽  
Decision Makers ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Similarity Learning ◽  
Reasoning System ◽  
Siamese Networks ◽  
Case Based

AbstractAquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely operate than are traditional sites. To help the industry deal with these challenges, we have developed a decision support system to support decision makers in establishing better plans and make decisions that facilitate operating these sites in an optimal manner. We propose a case-based reasoning system called aquaculture case-based reasoning (AQCBR), which is able to predict the success of an aquaculture operation at a specific site, based on previously applied and recorded cases. In particular, AQCBR is trained to learn a similarity function between recorded operational situations/cases and use the most similar case to provide explanation-by-example information for its predictions. The novelty of AQCBR is that it uses extended Siamese neural networks to learn the similarity between cases. Our extensive experimental evaluation shows that extended Siamese neural networks outperform state-of-the-art methods for similarity learning in this task, demonstrating the effectiveness and the feasibility of our approach.

scholarly journals Approximate case-based reasoning on neural networks

1994 ◽  
Vol 10 (1) ◽  
pp. 75-98 ◽  
Author(s):  
Zuliang Shen ◽  
Ho Chung Lui ◽  
Liya Ding
Keyword(s):  
Neural Networks ◽  
Case Based Reasoning ◽  
Case Based

scholarly journals HYBRID FORECASTING SYSTEM BASED ON CASE-BASED REASONING AND ANALYTIC HIERARCHY PROCESS FOR COST ESTIMATION

2013 ◽  
Vol 19 (1) ◽  
pp. 86-96 ◽  
Author(s):  
Sangyong Kim
Keyword(s):  
Analytic Hierarchy Process ◽  
Cost Estimation ◽  
Prediction Models ◽  
Early Stage ◽  
Case Based Reasoning ◽  
Cost Estimating ◽  
Analytic Hierarchy ◽  
Highway Projects ◽  
Hierarchy Process ◽  
Case Based

Cost estimating of highway projects with high accuracy at the early stage of project development is crucial for planning and feasibility studies. Various research have been attempted to develop cost prediction models in the early stage of a construction life cycle. This study uses the hybrid estimating tool to provide an effective cost data management for highway projects and accordingly develops a realistic cost estimating system. This study focused on the development of a more accurate estimate technique for highway projects in South Korea at the early stage using hybrid analytic hierarchy process (AHP) and case-based reasoning (CBR). Real case studies are used to demonstrate and validate the benefits of the proposed approach. It is expected that the developed CBR system is to provide decision-makers with accurate cost information to asses and compare multiple alternatives for obtaining the optimal solution and controlling cost.

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