Development of Neural-Risk Assessment Model for Successful Procurement of Road Projects

• 영문명: Development of Neural-Risk Assessment Model for Successful Procurement of Road Projects
• 발행기관: 한국구매조달학회
• 저자명: Muritala Adebayo Isaha Byung-Soo Kim
• 간행물 정보: 『한국구매조달학회지』제20권 제1호, 11~27쪽, 전체 17쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2021.06.30

영문 초록

Road infrastructural development is the bedrock for the social and economic development of any nation. However many developing nations including Nigeria still face the challenge of bridging the gaps in road infrastructure due to the impact of risk on project objectives leading to cost and time overruns or outright abandonment of the projects. This study is focused on the assessment of risk impact on road projects using a neural network approach. We developed neural-risk assessment models (NRAMs) using Keras application program interface(API) with the aid of Python programming language for the assessment of significant risk impact on the cost and time performance of road projects. The prediction of risk impact on the cost performance using NRAM revealed a mean operational error (MOE) of 64.26% for the ELU-linear model (ELM) indicating low accuracy while in time performance a MOE of 10.18% was observed for the softsign-linear model (SSLM) which indicates high accuracy. NRAM will assist the project managers in evaluating and predicting the impact of risk on the cost and time performance of road projects. Also, NRAM could be used as a decision support tool in the delivery process of road infrastructural projects in Nigeria and other developing countries.

목차

Introduction

Neural Network (NN)

NN for risk management

Activation function (AF)

Methodology

Data collection

Risk management

Development of NRAM

Model evaluation

Application of the model

Discussion of Results

Conclusion

Data Availability Statement

Acknowledgment

References

키워드

Risk management risk assessment risk impact neural network activation function time performance cost performance