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Moreover, this kind of model is traditionally used to describe the experimental phenomena of two-dimensional cross-section models, the gaps between the results of two-dimensional cross-section model tests and the prototype responses of the three-dimensional real structures should be filled up.
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With other models, the gap can be more drastic.
The model was derived from a forest gap model, reducing the gap models' complexity by model aggregation and includes elements for showing complex behavior: many state variables, non-linear process functions, feedbacks and spatial interactions.
Rossi and Meneguzzer [22] modeled the gap acceptance behavior at priority intersections using neuro-fuzzy system.
Maze [6] modeled the gap acceptance behavior using a logit model which closely approximates the probit model.
The results indicate that the ANFIS can be used to model the gap acceptance behavior at partially controlled intersections.
After careful observation, the following strategies have been adopted for modeling the gap acceptance behavior under mixed traffic condition using a logit model.
The primary focus of this paper is to model the gap acceptance behavior of vehicles at partially controlled intersections in India with the application of ANFIS.
Sangole et al. [11] used neuro-fuzzy technique to model the gap-acceptance behavior of right turning two wheelers (TWs) at three-legged intersections in India.
The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature.
Sangole et al. [16] used an adaptive neuro-fuzzy interface system (ANFIS) approach to model the gap acceptance behavior of two-wheelers at uncontrolled intersections.
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