Implementationof Artificial Neural Network for Recognition of Factors InfluencingLabor Production Rates for Concreting Activities– A Review

Journal Title: IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) - Year 2018, Vol 15, Issue 5

Abstract

Construction projects globally is considered to be multifaceted in nature. This complex work involves estimates of labor production rates during the planning as well as in the execution phase of the project. These estimates are habitually carried out by experienced personnel based on his/her experience, may sometimes not have the means to discern the controlling factor factors affecting the production rates. There are various trends in the soft computing techniques for identification of labor production rate in construction, and one being associated with Artificial Neural Networks (ANN). The current study emphasises on critical literature review on factors likely to affect the productivity rates for concreting activities like reinforcement installation, formwork installation and concreting placement and also some of the other industrial activities.

Authors and Affiliations

Mistry. Jignesh. Mukeshchandra, Dr. (Mrs. ) Geetha. K. Jayaraj

Keywords

Related Articles

Effect of Rice Husk Ash on the Compaction and Strength Properties of Shed Soil Treated With Carbide Lime and Sodium Hydroxide

The locally available shedi soil in Mangalore coast has been used in this investigation. The shedi soil which is also known as lithomargic soil is found to be problematic which is reported by many investigators due to it...

Risk Assessment of Critical Equipment Failure Mode. A Case Study of Olkaria 2 Geothermal Power Plant In Kenya.

Recently in Kenya, there is massive investment in exploration of geothermal energy which is the key source of power to the national grid. However, despite considerable investment in geothermal power sources, in Kenya and...

A Study on Stabilization of Expansive Soil with Ground Granulated Blast Furnace Slag and Flash

Soil stabilization is one of most important for the construction which is widely used in connection with pavements and structures because it improves the engineering properties of soil. Utilization of industrial waste ma...

Optimization of Drilling Parameters on Surface Roughness of Al 1200-SiC Composites Using Taguchi Analysis

In present study, the matrix material Al 1200 reinforced with various percentages (5% and 10%) of SiC particles. Stir casting method employed for producing AlSiC MMCs since it is simple and cheapest method used for produ...

Design and Fabrication of A Single Acting Hydraulic Crane

In this present work, the designed and fabrication of a single acting hydraulic crane was carried out. The hydraulic crane is made up of the following main components; the hydraulic actuator or actuating cylinder, the ma...

Download PDF file
  • EP ID EP438845
  • DOI 10.9790/1684-1505040714.
  • Views 74
  • Downloads 0

How To Cite

Mistry. Jignesh. Mukeshchandra, Dr. (Mrs. ) Geetha. K. Jayaraj (2018). Implementationof Artificial Neural Network for Recognition of Factors InfluencingLabor Production Rates for Concreting Activities– A Review. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), 15(5), 7-14. https://europub.co.uk/articles/-A-438845