scholarly journals Perceptive Factors That Affect Household Food Consumption Among Different Grassland Areas: A Case Study Based on Fuzzy Cognitive Map

2021 ◽  
Vol 9 ◽  
Author(s):  
Wanni Yang ◽  
Lin Zhen ◽  
Yunjie Wei ◽  
Yu Xiao

Food consumption acts as an intermediary between ecosystems and human systems in grassland areas. In this study, we generated a fuzzy cognitive map (FCM) to obtain a semi-quantitative assessment of impact factors on food consumption in the Xilin Gol Grassland, China, from the perception of local rural households. Based on it, the food consumption impact factors networks of households in Xilin Gol Grassland were created. Results showed that household recognition of food consumption impact factors differed among grassland transects in both amount and category, and the results of principal component analysis (PCA) ascertain such differences and transitions. Livestock breeding, income, local economic development, consumption habit, age, food price, and cost were the most important impact factors mentioned by both farmers and herdsmen. From south to north in the grassland transects, households' cognition of ecological and economic factors increased, and the cognition of personal and social factors decreased. Differences in supply, culture, customs, and socioeconomic characteristics affected the cognition of households and their livelihoods, which influenced impact factors as well as associated connections. The role of livestock breeding also validated the connection between human actives and the grassland ecosystem. Results from this study can be used as a reference for policymakers during decision-making processes respective of regional sustainable development.

2019 ◽  
Vol 208 ◽  
pp. 563-574 ◽  
Author(s):  
Piergiuseppe Morone ◽  
Pasquale Marcello Falcone ◽  
Antonio Lopolito

2017 ◽  
Vol 16 (8) ◽  
pp. 1807-1817 ◽  
Author(s):  
Fabiana Tornese ◽  
Maria Grazia Gnoni ◽  
Giorgio Mossa ◽  
Giovanni Mummolo ◽  
Rossella Verriello

Author(s):  
Elpiniki I. Papageorgiou ◽  
Antonis S. Billis ◽  
Christos Frantzidis ◽  
Evdokimos I. Konstantinidis ◽  
Panagiotis D. Bamidis

2021 ◽  
Vol 25 (4) ◽  
pp. 949-972
Author(s):  
Nannan Zhang ◽  
Xixi Yao ◽  
Chao Luo

Fuzzy cognitive maps (FCMs) have widely been applied for knowledge representation and reasoning. However, in real life, reasoning is always accompanied with hesitation, which is deriving from the uncertainty and fuzziness. Especially, when processing the online data, since the internal and external interference, the distribution and characteristics of sequence data would be considerably changed along with the passage of time, which further increase the difficulty of modeling. In this article, based on intuitionistic fuzzy set theory, a new dynamic intuitionistic fuzzy cognitive map (DIFCM) scheme is proposed for online data prediction. Combined with a novel detection algorithm of concept drift, the structure of DIFCM can be adaptively updated with the online learning scheme, which can effectively improve the representation of online information by capturing the real-time changes of sequence data. Moreover, in order to tackle with the possible hesitancy in the process of modeling, intuitionistic fuzzy set is applied in the construction of dynamic FCM, where hesitation degree as a quantitative index explicitly expresses the hesitancy. Finally, a series of experiments using public data sets verify the effectiveness of the proposed method.


2013 ◽  
Vol 91 ◽  
pp. 19-29 ◽  
Author(s):  
E.I. Papageorgiou ◽  
K.D. Aggelopoulou ◽  
T.A. Gemtos ◽  
G.D. Nanos

2021 ◽  
pp. 108119
Author(s):  
Mahdi Malakoutikhah ◽  
Moslem Alimohammadlou ◽  
Mehdi Jahangiri ◽  
Hadiseh Rabiei ◽  
Seyed Aliakbar Faghihi ◽  
...  

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