A priority-based intuitionistic multiplicative UTASTAR method and its application in low-carbon tourism destination selection

2020 ◽  
Vol 88 ◽  
pp. 106026 ◽  
Author(s):  
Cheng Zhang ◽  
Li Luo ◽  
Huchang Liao ◽  
Abbas Mardani ◽  
Dalia Streimikiene ◽  
...  
Keyword(s):  
Low Carbon ◽  
Tourism Destination ◽  
Destination Selection ◽  
A Priority

Biofuel Production and Its Implications in a Transitive Low Carbon Development Country

2018 ◽  
pp. 71-88
Author(s):  
Constant Labintan ◽  
Harald Winkler ◽  
Abiodun Elijah Obayelu
Keyword(s):  
Food Security ◽  
Sugar Beet ◽  
Grain Sorghum ◽  
Payback Period ◽  
Organic Content ◽  
Biofuel Production ◽  
Low Carbon ◽  
Emission Level ◽  
Food And Beverage ◽  
A Priority

This chapter explains the implication of South Africa's transport fuel 2% blending. Using dry grain sorghum as feedstock with guaranteed food security has lower emission of 24.93kg/ha with emerging farmers who constituted 30% of the suppliers with a 3-year payback period. Using irrigated sorghum with food security as a priority has a relatively lower emission level of 11.47kg/ha from emerging farmers with a 9-year payback period. Using sugar beet has lower emission level of 0.12kg/ha with emerging farmers and a 3-year payback period. Soil organic content has significant influence on emissions from land use practices. Commercial sugar beet ethanol production caused high emission (4.84kg/ha) but has a short payback period of only 2 years which enhanced household food consumption by 12.5% and 31.50% under food security not a priority and food security as a priority, respectively. In all, grain sorghum food and beverage gross domestic product (GDP) increased, respectively, by 8%, 0.19%, and 0.23% under food security as not a priority, and increased by 20.83%, 0.44%, and 0.61% in opposite scenario, respectively.

scholarly journals Tourism Destination Preference Prediction Based on Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Bin Deng ◽  
Jun Xu ◽  
Xin Wei
Keyword(s):  
Link Prediction ◽  
Prediction Accuracy ◽  
Prediction Method ◽  
Edge Computing ◽  
Prediction Methods ◽  
Random Forest Algorithm ◽  
Tourism Destination ◽  
Prediction Time ◽  
Weight Value ◽  
Destination Selection

In view of the fact that the important characteristics of tourism destination selection preference are not considered in the current prediction methods of tourism destination selection preference, resulting in low prediction accuracy and comprehensive accuracy and long prediction time, a tourism destination selection preference prediction method based on edge calculation is proposed. This paper uses edge computing to construct the characteristics of tourism destination selection preference and uses a random forest algorithm to select important features and carry out preliminary estimation and ranking. Using the multiple logit selection model, the tourists’ preference sequence for tourism destination selection is obtained and sorted and the tourism destination selection preference model is obtained. By calculating the weight value of tourism destination selection preference, the weight set of tourism destination selection preference is determined and the tourism destination selection preference is determined according to the link prediction method to realize the tourism destination selection preference prediction. The experimental results show that the comprehensive accuracy of the proposed method is good, which can effectively improve the prediction accuracy of tourism destination selection preference and shorten the prediction time of tourism destination selection preference.

scholarly journals Determinants of medical tourism destination selection process

2018 ◽  
Vol 27 (7) ◽  
pp. 775-794 ◽  
Author(s):  
Mohammadali Zolfagharian ◽  
Rajasree K Rajamma ◽  
Iman Naderi ◽  
Samaneh Torkzadeh
Keyword(s):  
Medical Tourism ◽  
Selection Process ◽  
Tourism Destination ◽  
Destination Selection

Optimized Tourism Destination Selection Based on InLinPreRa

2013 ◽  
Vol 774-776 ◽  
pp. 1786-1789
Author(s):  
Hsiu Fen Chen ◽  
Shu Chen Hsu ◽  
Ching Tien Shih
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Tourism Destination ◽  
Analytic Hierarchy ◽  
Preference Relations ◽  
Importance Weights ◽  
Speed Up ◽  
Destination Selection ◽  
Preference Matrix ◽  
Selection Of

This research is regarding the optimized tourism destination selection when tourists choose tourist products or travel destinations. This study adopts the method of Incomplete Linguistic Preference Relations to simplify calculation and speed up the process of comparison and selection of alternative. This method considers only judgments, whereas the tradition analytic hierarchy approach (AHP) takes judgments in a preference matrix with n elements to establish a complete preference relation decision making matrix. According to the importance weights of evaluationcriteria, C was the optimize tourism destination.

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