scholarly journals Assessing the performance and robustness of the UNICEF model for groundwater exploration in Ethiopia through application of the analytic hierarchy process, logistic regression and artificial neural networks

Water SA ◽  
2018 ◽  
Vol 44 (3 July) ◽  
Author(s):  
David Josephs-Afoko ◽  
Samuel Godfrey ◽  
Luiza C Campos
Keyword(s):  
Neural Networks ◽  
Logistic Regression ◽  
Artificial Neural Networks ◽  
Analytic Hierarchy Process ◽  
Groundwater Exploration ◽  
Analytic Hierarchy ◽  
Artificial Neural ◽  
The Analytic Hierarchy Process ◽  
Well Data ◽  
Hierarchy Process

This study assesses the performance and robustness of the groundwater potential (GWP) maps produced by the UNICEF model for deep groundwater exploration in Ethiopia. The UNICEF model is a weighted linear combination of hydrogeological parameters including permeability, slope, recharge, and lineament density, which has been calibrated using the expert judgements of local hydrogeologists. In order to assess the performance and robustness of the model, three techniques were employed: the analytic hierarchy process (AHP), logistic regression (LR), and artificial neural networks (ANNs). Three study areas (Dallol, Halaba and Shinelle) were selected on the basis of climatic and geological variation, in addition to the availability of well data pertaining to depth and yield. The performance of the UNICEF model in predicting outcomes of the well data included in the study was assessed by computing the receiver operating characteristic (ROC) curve. The solutions produced by the AHP and ANN were more accurate than the UNICEF model in determining the productivity of deep wells in the study data, whilst the LR model was less accurate than the UNICEF model. The groundwater productivity maps produced by the AHP and ANNs showed clear correlation with the maps produced by the UNICEF model, despite moderate (AHP) and severe (ANN) parameter perturbation, demonstrating the robustness of the UNICEF model. Whilst the AHP and ANN models demonstrated higher accuracy than the UNICEF model, this must be considered against the well data used to assess accuracy, which were drawn from a small sample of non-ideal distribution. Although this study focuses on case studies in Ethiopia the key findings are applicable internationally, namely, that the use of the AHP in data-scarce environments provides robust models, and that with the addition of easily obtainable well data the accuracy of modelling can be significantly increased through the application of ANNs.

scholarly journals A Partial-Consensus Posterior-Aggregation FAHP Method—Supplier Selection Problem as an Example

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 179 ◽  
Author(s):  
Yu-Cheng Wang ◽  
Tin-Chih Chen
Keyword(s):  
Supplier Selection ◽  
Pairwise Comparison ◽  
Selection Problem ◽  
Analytic Hierarchy ◽  
Comparison Results ◽  
Fuzzy Weights ◽  
Partial Consensus ◽  
Hierarchy Process ◽  
Supplier Selection Problem ◽  
Fuzzy Pairwise Comparison

Existing fuzzy analytic hierarchy process (FAHP) methods usually aggregate the fuzzy pairwise comparison results produced by multiple decision-makers (DMs) rather than the fuzzy weights estimations. This is problematic because fuzzy pairwise comparison results are subject to uncertainty and lack consensus. To address this problem, a partial-consensus posterior-aggregation FAHP (PCPA-FAHP) approach is proposed in this study. The PCPA-FAHP approach seeks a partial consensus among most DMs instead of an overall consensus among all DMs, thereby increasing the possibility of reaching a consensus. Subsequently, the aggregation result is defuzzified using the prevalent center-of-gravity method. The PCPA-FAHP approach was applied to a supplier selection problem to validate its effectiveness. According to the experimental results, the PCPA-FAHP approach not only successfully found out the partial consensus among the DMs, but also shrunk the widths of the estimated fuzzy weights to enhance the precision of the FAHP analysis.

scholarly journals Research on Supplier Selection of Prefabricated Building Elements from the Perspective of Sustainable Development

2021 ◽  
Vol 13 (11) ◽  
pp. 6080
Author(s):  
Yinghui Song ◽  
Junwu Wang ◽  
Feng Guo ◽  
Jiequn Lu ◽  
Sen Liu
Keyword(s):  
Sustainable Development ◽  
Analytic Hierarchy Process ◽  
Supplier Selection ◽  
Equation Model ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Analytic Hierarchy ◽  
Building Element ◽  
Hierarchy Process ◽  
Prefabricated Building

Prefabricated building is an efficient building mode. Compared with the traditional building mode, the prefabricated building has advantages of less pollution, high construction efficiency, being more labor-saving, and economy, which is in line with China’s sustainable development strategy. This paper proposes a supplier selection evaluation model based on the mechanism equation model (SEM) and intuitionistic fuzzy analytic hierarchy process (IFAHP). Based on a detailed literature review, 300 structured questionnaires were distributed to the relevant enterprises, and an evaluation index system of prefabricated building element suppliers was built. With the fitting and modification process using a structural equation model, and assist of a path factor, an evaluation index system for evaluating the prefabricated building element suppliers was finally obtained. Finally, the intuitionistic fuzzy analytic hierarchy process was used to establish a selection model of prefabricated element suppliers, and the prefabricated element suppliers of Shuangyashan prefabricated construction projects were analyzed as a case study. The results show that the following factors have the most significant impact on supplier selection (from high to low): quality, economy, long-term cooperation, after-sales, and transportation. This study had a comprehensive consideration of the influencing factors existing in the whole selection process and should provide a valuable reference for the sustainable development of prefabricated construction engineering.

Utilizing analytic hierarchy process for improved decision making within supply chains

2008 ◽  
Vol 27 (1) ◽  
pp. 49-62
Author(s):  
Sameer Kumar ◽  
John Bisson
Keyword(s):  
Analytic Hierarchy Process ◽  
Global Economy ◽  
Supplier Selection ◽  
Selection Process ◽  
Decision Support Tool ◽  
Data Availability ◽  
Analytic Hierarchy ◽  
Support Tool ◽  
Device Manufacturer ◽  
Hierarchy Process

With a growing global economy and competition and increased outsourcing, the supplier selection process has gained more focus and importance within many business enterprises for developing an integrated supply network. Analytic Hierarchy Process (AHP) has been identified as an ideal multi-objective decision support tool to assist firms in completing the supplier selection process as part of strengthening their procurement strategies. This paper involved secondary research methods to gain an understanding of AHP, its various applications, and exploration of how to incorporate non-traditional selection criteria such as environmental criterion into the process. AHP's application for optimal supplier selection to support integrated procurement process is illustrated through an example of a Medical Device Manufacturer (MDM), known for established supplier-customer partnerships and alliances. Major limitation in studying this example included data availability to complete a comprehensive AHP decision management model. However, it was found that AHP is a powerful, structured but flexible method of addressing the multi-criteria supplier selection decision that facilitates building an integrated supply chain.

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