A Comparative Study of Frequency Ratio, Shannon’s Entropy and Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility Assessment

Landslide susceptibility maps are very important tools in the planning and management of landslide prone areas. Qualitative and quantitative methods each have their own advantages and dis-advantages in landslide susceptibility mapping. The aim of this study is to compare three models, i.e., frequency ratio (FR), Shannon’s entropy and analytic hierarchy process (AHP) by implementing them for the preparation of landslide susceptibility maps. Shimla, a district in Himachal Pradesh (H.P.), India was chosen for the study. A landslide inventory containing more than 1500 landslide events was prepared using previous literature, available historical data and a field survey. Out of the total number of landslide events, 30% data was used for training and 70% data was used for testing purpose. The frequency ratio, Shannon’s entropy and AHP models were implemented and three landslide susceptibility maps were prepared for the study area. The final landslide susceptibility maps were validated using a receiver operating characteristic (ROC) curve. The frequency ratio (FR) model yielded the highest accuracy, with 0.925 fitted ROC area, while the accuracy achieved by Shannon’s entropy model was 0.883. Analytic hierarchy process (AHP) yielded the lowest accuracy, with 0.732 fitted ROC area. The results of this study can be used by engineers and planners for better management and mitigation of landslides in the study area.

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Application of Shannon’s entropy-analytic hierarchy process (AHP) for the selection of the most suitable starch as matrix in green biocomposites for takeout food packaging design

BioResources ◽

10.15376/biores.15.2.4065-4088 ◽

2020 ◽

Vol 15 (2) ◽

pp. 4065-4088

Author(s):

H. N. Salwa ◽

S. M. Sapuan ◽

M. T. Mastura ◽

M. Y. M. Zuhri

Keyword(s):

Analytic Hierarchy Process ◽

Food Packaging ◽

Shannon’S Entropy ◽

Rice Starch ◽

Sago Starch ◽

Analytic Hierarchy ◽

Design Elements ◽

Packaging Design ◽

Shannon's Entropy ◽

Hierarchy Process

Starch is a natural polymer and eligible for short-term, single-use food packaging applications. Nevertheless, different starches have different features and properties determined by their botanical plant origins. This paper presents an approach that combines Shannon’s entropy and the Analytic Hierarchy Process method to aid the selection process of starch as matrix in green biocomposites for takeout food packaging design. The proposed selection system ranks alternative starches in terms of the key design elements, i.e. strength, barrier property, weight, and cost. Shannon’s entropy established corresponding weight values for the indicators selected. Six starches: wheat, maize, potato, cassava, sago, and rice were appraised using gathered data from the literature to determine their suitability as a more sustainable option. This study found that sago starch obtained the highest priority score of 26.8%, followed by rice starch (20.2%). Sensitivity analysis was then carried out to further verify the results; sago starch was at the top rank for five of six different scenarios tested. The results showed that sago starch is the starch that can best satisfy the design requirements. Despite the results attained, the selection framework used could be enhanced with a more comprehensive attributes assessment and extensive dataset.

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