• Title/Summary/Keyword: GeoANFIS

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Application of the optimal fuzzy-based system on bearing capacity of concrete pile

  • Kun Zhang;Yonghua Zhang;Behnaz Razzaghzadeh
    • Steel and Composite Structures
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    • v.51 no.1
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    • pp.25-41
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    • 2024
  • The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFISFHO and ANFISEO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFISFHO and ANFISEO both have amazing potential for precisely calculating pile bearing capacity. The R2 values obtained for ANFISFHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFISFHO system had less uncertainty than the ANFISEO model. The research found that the ANFISFHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

A Study on Real-Time Operation Method of Urban Drainage System using Data-Driven Estimation (실시간 자료지향형 예측을 활용한 내배수 시설 운영기법 연구)

  • Son, Ahlong;Kim, Byunghyun;Han, Kunyeun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.6
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    • pp.949-963
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    • 2017
  • This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.