Cost Prediction and managment Research Papers (original) (raw)

Monte Carlo Simulation is a mathematical technique that generates random variables for modelling risk. This technique is suitable and benefits to the various client such as public and private sector to evaluate the realistic costing proposed by the Quantity Surveyor. Through this approach, quality of life received by the client in investing budget without waste of propose funding in the construction project. The methodology used is a qualitative approach consist of case study and document analysis. The result shows through Monte Carlo simulation, can predict the worst return from the accuracy of the estimation and given absolute confidence for project development. Keywords: Monte Carlo, Risk Analysis, Cost Prediction, Qualitative Approach eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under re...

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- Computer Science, Monte Carlo, Quality of life, Risk Analysis

This paper addresses the gap in the scientific literature regarding construction cost estimates for the construction of underground metro stations. It provides preliminary cost estimation models using linear regression for use by the Greek underground metro public transport authority for planning future extensions to the Athens and Thessaloniki networks. At the same time, it contributes to the body of knowledge by proposing material quantity prediction models and presents a two-stage preliminary cost estimation model for the construction of civil engineering works of underground metro stations. Stage one uses the construction cost budgets of six metro stations in Greece to develop a multilinear regression equation for the prediction of the overall cost for construction of civil engineering works; stage two provides estimates of material quantities using linear regression, key quantity ratios, and artificial neural networks. The data analyzed are from the prior measurements of quanti...

Monte Carlo Simulation is a mathematical technique that generates random variables for modelling risk. This technique is suitable and benefits to the various client such as public and private sector to evaluate the costing prepared by the Quantity Surveyor. The methodology used is a qualitative approach consisting of a case study and document analysis. The result shows through Monte Carlo simulation, can predict the worst return from the accuracy of the estimation and given absolute confidence for project development.

- by DR. MOHAMAD SUFIAN HASIM
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- Computer Science, Monte Carlo Method

- by DR. MOHAMAD SUFIAN HASIM
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- Computer Science, Monte Carlo, Quality of life, Risk Analysis

Predictive Analytics and Decision Support for Heart Failure patients Aftab Hassan Chair of the Supervisory Committee: Assistant Professor Senjuti Basu Roy Institute of Technology In the last few years, legislations such as the Patient Protection and Affordable Care Act, also known as Obamacare, have emphasised the need for improving the quality of health care. Part of the programs introduced by this Act is the Hospital Readmissions Reduction Program (HRRP) which reduces payments to hospitals with excess readmissions. Hospitals are, therefore, constantly looking for ways to help reduce their readmission rate, and an idea of patients that are at a higher risk of getting readmitted is extremely beneficial. In this thesis, we first look at ways to predict the chance of a patient getting readmitted, and investigate predicting future healthcare costs, to understand how much money the patient would have to spend on hospital expenses during the readmission visit. We, then design a multi obj...

- by Aftab Hassan
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- Computer Science, Artificial Intelligence, Health Care Management, Bayesian Networks

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

- by Hafiszah Ismail
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- Computer Science, Monte Carlo, Quality of life, Risk Analysis
- by Hennie Huijgens
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- Engineering, Computer Science, Benchmarking, Cost Prediction and managment

Monte Carlo Simulation is a mathematical technique that generates random variables for modelling risk. This technique is suitable and benefits to the various client such as public and private sector to evaluate the costing prepared by the Quantity Surveyor. The methodology used is a qualitative approach consisting of a case study and document analysis. The result shows through Monte Carlo simulation, can predict the worst return from the accuracy of the estimation and given absolute confidence for project development. Keywords: Monte Carlo, Risk Analysis, Cost Prediction, Qualitative Approach eISSN 2398-4279 ©2020 The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs ...

- by mohamad sufian hasim
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- Computer Science, Monte Carlo Method

- by mohamad sufian hasim
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- Computer Science, Monte Carlo, Quality of life, Risk Analysis

- by Hafiszah Ismail
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- Computer Science, Monte Carlo, Quality of life, Risk Analysis
- by Allen Y. Chang
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- Computational Geometry, Pure Mathematics, Cost Model, Ray Tracing
- by Abraham Deme
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- Path Loss

Regression analysis is used across business fields for tasks as diverse as systematic risk estimation, production and operations management, and statistical inference. This paper presents the cubic polynomial least square regression as a robust alternative method of making cost prediction in business rather than the usual linear regression.The study reveals that polynomial regression is a better alternative with a very high coefficient of determination. Keywords: Polynomial regression, linear regression, high-low method, cost prediction, mixed cost.

- by Abdullahi Adedeji
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- Mathematics

There is a dearth of information on the comparative costs of projects carried out using the main procurement building systems. This paper reports the feasibility study of a research programme to produce a computer-based neural network cost model to show the effect on client costs of ?inter alia? using different procurement approaches. A literature search identified 39 cost-significant project variables. Data were collected from collaborating QS practices, resulting in 46 project data-sets with which to test various modelling approaches. Evaluation of the data and model objectives identified multiple regression and neural networks as potential model forms. Investigation and trials of both have shown that regression and neural networks can provide effective representation of the client costs model but neural networks, due to their greater ability in modelling interdependencies between input variables, modelling non-linear relationships, and handling incomplete data sets, will probably...

- by Margaret Emsley
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- Engineering, Procurement, Neural Networks, Cost modelling

The authors have considered a complex system consisting of two subsystems designated as ‘A’ and ‘B’ connected in series. Subsystem ‘A’ consists of N non-identical units in series, while the subsystem ‘B’ consists of three identical components in parallel redundancy. Keywords: Availability/Reliability Analysis, Repairable Parallel System, Laplace transform, cost profit function, Head-of-line Repair,

- by sonendra Gupta
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- by Danjuma Dajab
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- by Charles Wahogo
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There is a dearth of information on the comparative costs of projects carried out using the main procurement building systems. This paper reports the feasibility study of a research programme to produce a computer-based neural network cost model to show the effect on client costs of ‘inter alia’ using different procurement approaches.
A literature search identified 39 cost-significant project variables. Data were collected from collaborating QS practices, resulting in 46 project data-sets with which to test various modelling approaches.
Evaluation of the data and model objectives identified multiple regression and neural networks as potential model forms. Investigation and trials of both have shown that regression and neural networks can provide effective representation of the client costs model but neural networks, due to their greater ability in modelling interdependencies between input variables, modelling non-linear relationships, and handling incomplete data sets, will probably be the better choice with which to analyse the very much larger volume of data planned for the next phase of the research.
The results have demonstrated that such a model can be developed, that data to support it can be obtained and, additionally, that the utility of the model may be significantly greater than had been envisaged at the start of the study.

The use of an effective feedback system is considered to influence the quality of estimates. Similarly, it is held that a means of monitoring performance should be incorporated into any forecasting system. Moreover, on an individual basis, systematic reflection is considered crucial for effective experiential learning. It is suggested that only through some process of systematic reflection may a professional achieve growth and self-renewal.
This paper examines the application of effective feedback systems and systematic reflection by early stage design cost estimators. The findings from a fully structured interview survey of experienced early stage design cost estimators (n = 84) and a questionnaire survey of student quantity surveyors (n = 331) are presented.
Despite the recommendations of previous studies, many practitioners still have inadequate feedback systems. Many either did not systematically reflect on the outcomes of estimates, or used self-assessment as the sole means of evaluation. Also, practitioners had significantly lower Reflective Observation learning style scores when compared to the student sample, while their declared approach to learning exhibited a reluctance for self-assessment or self-appraisal. Finally, on an organisational basis both practitioners and student quantity surveyors gave a low rating to the provision of constructive feedback by the organisation on their performance.

- by David J Lowe
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- Quantity Surveying, Reflection, Experiential Learning, Feedback

A successful pilot study, applying computer simulation of the human brain to the prediction of the whole range of client costs of building projects, has been carried out by a team from the UMIST Department of Building Engineering. The study, funded by The Engineering & Physical Sciences Research Council (EPSRC), demonstrated that the total costs of procurement, including client administration, consultant’s fees and construction, can be modelled by a new type of computer software called neural networks.

- by Seyi Ajao
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- Cost Prediction and managment, Linear Regression, Polynomial Regression

Abstract: The focus of this paper is on the influence of the learning climate in organisations on practitioner competence. Practitioners in the context of the paper are Chartered Quantity Surveyors, while competency is measured in terms... more

- by Martin Skitmore
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- by Alexander Decker
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