Vulnerability of Watersheds to Climate Change Assessed by Neural Network and Analytical Hierarchy Process

2016 ◽  
Author(s):  
Uttam Roy ◽  
Mrinmoy Majumder
Keyword(s):  
Neural Network ◽  
Climate Change ◽  
Analytical Hierarchy Process ◽  
Hierarchy Process

scholarly journals Water resilience mapping of Chennai, India using analytical hierarchy process

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
R. Kaaviya ◽  
V. Devadas
Keyword(s):  
Climate Change ◽  
Analytical Hierarchy Process ◽  
Tamil Nadu ◽  
Water Resource Management ◽  
Global Climate ◽  
Decision Matrix ◽  
Analysis Technique ◽  
Study Results ◽  
Chennai City ◽  
Hierarchy Process

Abstract Background The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP). Methods The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes. Results Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications. Conclusion This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures.

scholarly journals Applying Analytic Hierarchy Process to Adaptation to Saltwater Intrusion in Vietnam

2021 ◽  
Vol 13 (4) ◽  
pp. 2311
Author(s):  
Thi Dieu Linh Nguyen ◽  
Brent Bleys
Keyword(s):  
Climate Change ◽  
Focus Group ◽  
Analytical Hierarchy Process ◽  
Saltwater Intrusion ◽  
Coastal Region ◽  
Pairwise Comparison ◽  
Focus Group Discussions ◽  
Group Discussions ◽  
Hierarchy Process ◽  
Adaptation Options

Given the multidimensional nature of climate change issues, decision-making in climate change adaptation is a complex process, and suitable decision support methods are needed. The aim of this paper was to rank saltwater intrusion adaptation options for farmers in two provinces in the central coastal region of Vietnam using the analytical hierarchy process method. Data for the analysis were obtained through a literature review, field observations, and face-to-face interviews and focus group discussions with key informants. We combined two ways of weighting to arrive at final scores for each of the identified adaptation options: prioritizing criteria and subcriteria by pairwise comparison and rating the different alternatives with respect to the lowest level subcriteria. In doing so, we also investigated differences in the priority sets and final rankings of the analytical hierarchy process applications in both provinces. In our study, we worked with group consensus scores on both the criteria weights and the ratings for the different adaptation options for each of the criteria. Our results revealed that “sustainability and equity” was the most important criteria, while coherence ranked lowest. The final ranking of adaptation options differed between both provinces due to differences in the geographical and socioeconomic characteristics of the study areas. The consistency ratios for all pairwise matrices were less than 0.1, indicating that judgments from the focus group discussions with respect to the different criteria were highly consistent. A sensitivity analysis of our results confirmed the robustness of the rankings in our research.

scholarly journals Artificial Neural Network and Analytical Hierarchy Process Integration: A Tool to Estimate Business Strategy of Bank

2020 ◽  
Vol 11 (1) ◽  
pp. 66-66
Author(s):  
Mochammad Ridwan Ristyawan
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Artificial Neural Network ◽  
Analytical Hierarchy Process ◽  
Business Strategy ◽  
Business Environment ◽  
Strategic Resources ◽  
Inductive Algorithm ◽  
Artificial Neural ◽  
Hierarchy Process

The disruption has been occurring in financial services. Rethinking new strategy of banking is needed to make a sustainable competitive advantage innovation in organizations. The four types of business strategy for banks are prospector, analyzer, defender, and reactor. Studies mentioned that formulating strategy is very costly, time consuming, and comprehensive analysis. The banks have to get rid of execution time inefficiency, lack of flexibility, and lack of ability to present several scenarios in the dynamic business environment. The purpose of this study is to present an integrated intelligence algorithm for estimating strategic resources of the bank strategy in Indonesia. The algorithm has two basic modules which are artificial neural network (ANN) and analytical hierarchy process (AHP). ANN is utilized as an inductive algorithm in discovering predictive strategy of the bank and used to explain the strategic resources which improved in forward. AHP has the capability to handle multi-level decision-making structure with use of expert judgments in pairwise comparison process. AHP is used to measure the weight of the resources and the score is used to determine the strategy. The empirical results indicate that ANN and AHP integration is proved to predict the business strategy of the bank. The strategy choice appropriate with the condition of bank's resources. This framework can be implemented to help banker for the decision making in bank operation. Keywords: business strategy, ANN, AHP, resources

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