STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

Selection of Tower Cranes through ANN (Artificial Neural Network) Model

  1. Vidhi Munshaw
  2. Jyoti Trivedi

Abstract

In India, the construction sector has been increased due to large spending on the infrastructures in last few years. By such growth in infrastructure, rising trend of precast technology for real estate construction and high rise construction, there is a drive growth of the Indian tower crane industry. With the increasing demand of tower cranes, the selection of the suitable tower crane for a particular site also becomes important; as selection of appropriate tower crane can have a significant influence on time, cost and safety of construction operation and it also will govern the selection of other equipment’s. And also, there is an address of improvement for deployment of equipment in the five year plan. Many models are developed for selection but none has quantified them. Fuzzy logic and expert system based methods for mobile crane type selection has also been suggested. But no comprehensive and integrated systems are available, which can even select a given model for a given type of mobile crane and tower cranes. Further, these models have considered the productivity and cost factor, but not the safety and environmental factors for the selection of the equipment. This paper presents the factors to be considered while selection of a tower crane for a particular construction site; and the significance of each factor were found out using regression analysis through SPSS software and Matlab by ANN (Artificial Neural Network) tool. Factors such as project duration, project cost, site area, maximum height, number of towers, accessibility, availability of the space on site, terrain type of the site, availability of power lines, soil bearing capacity, maximum load to be carried on site, type of material to be lifted on site, storage yard location, relocation on site, safety and quality conditions specified by the client, cost of the tower crane are taken into consideration during preparation of the model. Also, an integrated tower crane selection model is prepared which helps in selection of; the type and model selection of tower crane, using historical data, case studies and pattern recognition tool of ANN model in Matlab. Cite this Article Vidhi Munshaw, Jyoti Trivedi. Selection of Tower Cranes through ANN (Artificial Neural Network) Model. Journal of Image Processing & Pattern Recognition Progress. 2016; 3(2): 67–79p.

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