Key indexes choosing approach of complex equipment’s development cost based on grey incidence cluster model

2016 ◽  
Vol 6 (1) ◽  
pp. 110-123 ◽  
Author(s):  
Naiming Xie ◽  
Chuanzhen Hu ◽  
Songming Yin
Keyword(s):  
Cost Estimation ◽  
Grey System Theory ◽  
Critical Parameters ◽  
Estimation Accuracy ◽  
Content Type ◽  
Complex Products ◽  
Civil Aircraft ◽  
Complex Equipment ◽  
Key Indicators ◽  
The Cost

Purpose – The purpose of this paper is to establish a combined model for selecting key indexes of complex equipment, and then improve the cost forecasting precision of the model. The problem how to choose the key elements of complex products has always been concerned on many fields, such as cost assessment, investment decision making, etc. Design/methodology/approach – Using Grey System Theory to establish a cost estimation model of complicated equipment is more reasonable under the few data and poor information. Therefore, this paper constructs cost index’s system of complex equipment, and then quantitative and qualitative analysis methods are utilized to calculate the grey entropy between the characteristic parameter and the behavior parameters. Further, establish the grey relational clustering matrix of the behavior sequences by using the grey relative incidence analysis. Finally, the authors select key indicators according to the grey degree. Findings – The experiment demonstrates that the cost key parameters of complex equipment can be successfully screened out by the proposed approach, and the cost estimation accuracy of complicated products is improved. Practical implications – The method proposed in this paper could be utilized to solve some practical problems, particularly the selection of cost critical parameters for complex products with few samples and poor information. Taking the cost key indexes of civil aircraft as an example, the results verified the validity of the GICM model. Originality/value – In this paper, the authors develop the method of GICM model. Taking the data of civil aircraft as an example, the authors screen the key indicators of complex products successfully, and improve the prediction accuracy of the GM (1, N) model by using the selected parameters, which provides a reference for some firms.

scholarly journals Improving the cost estimates of complex projects in the project-based industries

2017 ◽  
Vol 7 (2) ◽  
pp. 173-184 ◽  
Author(s):  
Pournima Sridarran ◽  
Kaushal Keraminiyage ◽  
Leon Herszon
Keyword(s):  
Best Practices ◽  
Cost Estimation ◽  
Estimation Accuracy ◽  
Effective Practices ◽  
Accurate Estimation ◽  
Content Type ◽  
Complex Projects ◽  
Cost Implications ◽  
The Cost ◽  
Improve Cost

Purpose Project-based industries face major challenges in controlling project cost and completing within the budget. This is a critical issue as it often connects to the main objectives of any project. However, accurate estimation at the beginning of the project is difficult. Scholars argue that project complexity is a major contributor to cost estimation inaccuracies. Therefore, recognising the priorities of acknowledging complexity dimensions in cost estimation across similar industries is beneficial in identifying effective practices to reduce cost implications. Hence, the purpose of this paper is to identify the level of importance given to different complexity dimensions in cost estimation and to recognise best practices to improve cost estimation accuracy. Design/methodology/approach An online questionnaire survey was conducted among professionals including estimators, project managers, and quantity surveyors to rank the identified complexity dimensions based on their impacts in cost estimation accuracy. Besides, in-depth interviews were conducted among experts and practitioners from different industries, in order to extract effective practices to improve the cost estimation process of complex projects. Findings Study results show that risk, project and product size, and time frame are the high-impact complexity dimensions on cost estimation, which need more attention in reducing unforeseen cost implications. Moreover, study suggests that implementing a knowledge sharing system will be beneficial to acquire reliable and adequate information for cost estimation. Further, appropriate staffing, network enhancement, risk management, and circumspect estimation are some of the suggestions to improve cost estimation of complex projects. Originality/value The study finally provides suggestions to improve cost estimation in complex projects. Further, the results are expected to be beneficial to learn lessons from different industries and to exchange best practices.

scholarly journals Construction tender price estimation standardization (TPES) in Malaysia

2018 ◽  
Vol 25 (3) ◽  
pp. 443-457 ◽  
Author(s):  
Salihudin Hassim ◽  
Ratnasamy Muniandy ◽  
Aidi Hizami Alias ◽  
Pedram Abdullah
Keyword(s):  
Neural Network ◽  
Coming Out ◽  
Cost Estimation ◽  
Influential Factors ◽  
Estimation Accuracy ◽  
Content Type ◽  
Estimation Process ◽  
Price Estimation ◽  
Fuzzy Neural ◽  
Artificial Neural Network Method

Purpose The pre-tender estimation process is still a hazy and inaccurate process, despite it has been practiced over decades, especially in Malaysia. The methods evolved over time largely depend on the amount of information available at the time of estimation. More often than not, the estimate produced during the pre-tender stage is far more than the tender cost of the project and sometimes, it is perilously underestimated and caused major problems to the client in the monetary planning. The purpose of this paper is to determine the most influential factors on the deviation of pre-tender cost estimation in Malaysia by conducting a survey. Design/methodology/approach Fuzzy logic, combined with artificial neural network method (fuzzy neural network) was then used to develop an estimating model to aid the pre-tender estimation process. Findings The results showed that the model is able to shift the cost estimation toward accuracy. This model can be used to improve the pre-tender estimation accuracy, enabling the client to take the necessary early measures in preparing the funding for a building project in Malaysia. Originality/value To the authors’ knowledge, this is the first study on tender price estimation standardization for a construction project in Malaysia. In addition, the authors have used factors from literature for the model, which shows the thoroughness of the developed model. Thus, the findings and the model developed in this study should be able to assist contractors in coming out with a more accurate tender price estimation.

A grey rough set model for evaluation and selection of software cost estimation methods

2014 ◽  
Vol 4 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jun Liu ◽  
Jian-Zhong Qiao
Keyword(s):  
System Theory ◽  
Rough Set ◽  
Cost Estimation ◽  
Estimation Method ◽  
Grey System Theory ◽  
Estimation Methods ◽  
Software Cost Estimation ◽  
Grey System ◽  
Software Cost ◽  
Content Type

Purpose – Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs. Design/methodology/approach – Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness. Findings – The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided. Practical implications – Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method. Originality/value – This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.

Estimating Activity Costs: How the Provision of Accurate Historical Activity Data from a Biased Cost System Can Improve Individuals' Cost Estimation Accuracy

2007 ◽  
Vol 19 (1) ◽  
pp. 133-159 ◽  
Author(s):  
Dan L. Heitger
Keyword(s):  
Cost Estimation ◽  
Estimation Accuracy ◽  
Activity Data ◽  
Research Attention ◽  
Cost System ◽  
Initial Cost ◽  
Activity Cost ◽  
Historical Activity ◽  
The Cost ◽  
Activity Costs

An integral component of effective cost control and performance evaluation is the ability to accurately estimate relationships between activities and overhead costs (i.e., activity costs). Individuals using a single cost pool system often have to rely on memory of historical activity data when estimating activity costs. If individuals' recall of data is representative of the historical data, then reliance on memory should not be detrimental to cost estimation accuracy. However, individuals often possess incorrect initial beliefs about activity costs. These incorrect beliefs are expected to serve as an anchor from which individuals make insufficient adjustments when estimating activity costs based on memory of historical activity data. Multiple cost pool systems frequently provide biased standard rates; however, such systems also provide accurate historical activity data when individuals estimate costs. I extend prior accounting research by experimentally examining whether a multiple cost pool system's provision of accurate historical activity data improves activity cost estimation for individuals with incorrect cost beliefs even when the cost system also provides biased standard rates. The main contribution of the study is its finding that the multiple cost pool system's provision of historical activity data improves individuals' adjustments from their incorrect initial cost beliefs when estimating activity costs, thereby increasing their estimation accuracy. The results suggest that this improved adjustment from incorrect initial cost beliefs occurs because the provision of historical activity data improves individuals' recognition of how wrong their initial cost beliefs were in reality. This result is achieved even though the cost system provides biased standard rates. The ability of flawed cost systems to improve individuals' activity cost estimation in other such ways has received little research attention and is important because of its potential for improving managerial decision making.

Cost analysis error? Exploring issues relating to whole-life cost estimation in sustainable housing

2014 ◽  
Vol 19 (1) ◽  
pp. 4-23 ◽  
Author(s):  
Brian Sloan ◽  
Olubukola Tokede ◽  
Sam Wamuziri ◽  
Andrew Brown
Keyword(s):  
Cost Estimation ◽  
Cost Models ◽  
Binomial Theorem ◽  
Value Analysis ◽  
Content Type ◽  
Zero Carbon ◽  
The Cost ◽  
Whole Life Costing ◽  
The Impact ◽  
Whole Life Cost

Purpose – The main purpose of the study is to promote consideration of the issues and approaches available for costing sustainable buildings with a view to minimising cost overruns, occasioned by conservative whole-life cost estimates. The paper primarily looks at the impact of adopting continuity in whole-life cost models for zero carbon houses. Design/methodology/approach – The study embraces a mathematically based risk procedure based on the binomial theorem for analysing the cost implication of the Lighthouse zero-carbon house project. A practical application of the continuous whole-life cost model is developed and results are compared with existing whole-life cost techniques using finite element methods and Monte Carlo analysis. Findings – With standard whole-life costing, discounted present-value analysis tends to underestimate the cost of a project. Adopting continuity in whole-life cost models presents a clearer picture and profile of the economic realities and decision-choices confronting clients and policy-makers. It also expands the informative scope on the costs of zero-carbon housing projects. Research limitations/implications – A primary limitation in this work is its focus on just one property type as the unit of analysis. This research is also limited in its consideration of initial and running cost categories only. The capital cost figures for the Lighthouse are indicative rather than definitive. Practical implications – The continuous whole-life cost technique is a novel and innovative approach in financial appraisal […] Benefits of an improved costing framework will be far-reaching in establishing effective policies aimed at client acceptance and optimally performing supply chain networks. Originality/value – The continuous whole-life costing pioneers an experimental departure from the stereo-typical discounting mechanism in standard whole-life costing procedures.

F-ONTOCOM: A Fuzzified Cost Estimation Approach for Ontology Engineering

2021 ◽  
Author(s):  
Sonika Malik ◽  
Sarika Jain
Keyword(s):  
Cost Estimation ◽  
Evaluation Criteria ◽  
Ontology Engineering ◽  
Estimation Accuracy ◽  
Effort Estimation ◽  
Wide Scale ◽  
Ontology Building ◽  
The Cost ◽  
Essential Prerequisite ◽  
Estimation Models

Estimating effort is an essential prerequisite for the wide-scale dispersal of ontologies. Not much attention has yet been paid to this essential aspect of ontology building. To date, ONTOCOM is the most prominent model for ontology cost estimation. Many factors influencing the building cost of an ontology are depicted by linguistic terms like Very High, High, . . . and so on; making them vague and indistinct. This fuzziness is quite uncertain and must be taken into consideration. The available effort estimation models do not consider the uncertainty of fuzziness. In this work, we propose an effort estimation methodology for ontology engineering using Fuzzy Logic i.e. F-ONTOCOM (Fuzzy-ONTOCOM) to overcome of uncertainty and imprecision. We have defined the corresponding Fuzzy sets for each effort multiplier and its associated linguistic value, and represented the same by triangular membership functions. F-ONTOCOM is applied to a dataset of 148 ontology projects and evaluated over various evaluation criteria. FONTOCOM outperforms the existing effort-estimation models; it has been concluded that F-ONTOCOM improves the cost estimation accuracy and estimated cost is very close to actual cost.

Wavelet transform-based steganographic method for secure data communication using OFDM system

2017 ◽  
Vol 10 (3) ◽  
pp. 362-386 ◽  
Author(s):  
Sanjay I. Nipanikar ◽  
V. Hima Deepthi
Keyword(s):  
Wavelet Transform ◽  
Cost Estimation ◽  
Communication System ◽  
Data Communication ◽  
Extraction Process ◽  
Cover Image ◽  
The Novel ◽  
Ofdm System ◽  
Content Type ◽  
The Cost

Purpose Fueled by the rapid growth of internet, steganography has emerged as one of the promising techniques in the communication system to obscure the data. Steganography is defined as the process of concealing the data or message within media files without affecting the perception of the image. Media files, like audio, video, image, etc., are utilized to embed the message. Nowadays, steganography is also used to transmit the medical information or diagnostic reports. The paper aims to discuss these issues. Design/methodology/approach In this paper, the novel wavelet transform-based steganographic method is proposed for secure data communication using OFDM system. The embedding and extraction process in the proposed steganography method exploits the wavelet transform. Initially, the cost matrix is estimated by the following three aspects: pixel intensity, edge transformation and wavelet transform. The cost estimation matrix provides the location of the cover image where the message is to be entrenched. Then, the wavelet transform is utilized to embed the message into the cover image according to the cost value. Subsequently, in the extraction process, the wavelet transform is applied to the embedded image to retrieve the message efficiently. Finally, in order to transfer the secret information over the channel, the newly developed wavelet-based steganographic method is employed for the OFDM system. Findings The experimental results are evaluated and performance is analyzed using PSNR and MSE parameters and then compared with existing systems. Thus, the outcome of our wavelet transform steganographic method achieves the PSNR of 71.5 dB which ensures the high imperceptibility of the image. Then, the outcome of the OFDM-based proposed steganographic method attains the higher PSNR of 71.07 dB that proves the confidentiality of the message. Originality/value In the authors’ previous work, the embedding and extraction process was done based on the cost estimation matrix. To enhance the security throughout the communication system, the novel wavelet-based embedding and extraction process is applied to the OFDM system in this paper. The idea behind this method is to attain a higher imperceptibility and robustness of the image.

Estimating a civil aircraft’s development cost with a GM(1, N) model and an MLP neural network

2017 ◽  
Vol 7 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Nai-ming Xie ◽  
Song-Ming Yin ◽  
Chuan-Zhen Hu
Keyword(s):  
Neural Network ◽  
Cost Estimation ◽  
Development Cost ◽  
Combined Approach ◽  
Limited Data ◽  
New Approach ◽  
Content Type ◽  
Development Costs ◽  
Civil Aircraft ◽  
New Type

Purpose The purpose of this paper is to study a new approach by combining a multilayer perceptron neural network (MLPNN) algorithm with a GM(1, N) model in order to estimate the development cost of a new type of aircraft. Design/methodology/approach First, data about developing costs and their influencing factors were collected for several types of Boeing and Airbus aircraft. Second, a GM(1, N) model was constructed to simulate development costs for a civil aircraft. Then, an MLPNN algorithm was added to optimize and revise the simulative and forecasting values. Finally, a combined approach, using both a GM(1, N) model and an MLPNN algorithm was adopted to forecast development costs for new civil aircraft. Findings The results show that the proposed approach could do the work of cost estimation for new types of aircraft. Rather than using a single model, the combined approach could improve simulative and forecasting accuracy. Practical implications Scientific cost estimation could improve management efficiency and promote the success of a new type of civil aircraft development. Considering that China’s civil aircraft research and development is at its very beginning stages, only very limited data could be collected. The development costs for civil aircraft are affected by a series of factors. The approach outlined by this paper could be applied to development cost estimations in China’s civil aircraft industry. Originality/value The paper has succeeded by constructing a cost estimation index system and proposing a novel combined cost estimation approach comprised of a GM(1, N) model and an MLPNN. It has undoubtedly contributed to improving the accuracy of cost estimations.

Estimation of construction project building cost by back-propagation neural network

2019 ◽  
Vol 18 (3) ◽  
pp. 601-609
Author(s):  
Qinghua Jiang
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Bp Neural Network ◽  
Cost Estimation ◽  
Back Propagation ◽  
Estimation Accuracy ◽  
Average Error ◽  
Estimation Model ◽  
Content Type ◽  
Building Cost

Purpose Building cost is an important part of construction projects, and its correct estimation has important guiding significance for the follow-up decision-making of construction units. Design/methodology/approach This study focused on the application of back-propagation (BP) neural network in the estimation of building cost. First, the influencing factors of building cost were analyzed. Six factors were selected as input of the estimation model. Then, a BP neural network estimation model was established and trained by ten samples. Findings According to the experimental results, it was found that the estimation model converged at about 85 times; compared with radial basis function (RBF), the estimation accuracy of the model was higher, and the average error was 5.54 per cent, showing a good reliability in cost estimation. Originality/value The results of this study provide a reliable basis for investment decision-making in the construction industry and also contribute to the further application of BP neural network in cost estimation.

An intelligent pre-estimation method of design time for complex products based on v-SVM

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yujie Zheng ◽  
Meiyan Li
Keyword(s):  
Evaluation Model ◽  
Estimation Method ◽  
Estimation Accuracy ◽  
Task Characteristics ◽  
Adaptive Genetic Algorithm ◽  
Content Type ◽  
Design Task ◽  
Complex Products ◽  
Design Time ◽  
Method Of Design

Purpose Improving the prediction accuracy of design time for complex products is significant for improving the accuracy of product development and control plans. The purpose of this study is to propose an intelligent pre-estimation method of design time for complex products based on v-SVM. Design/methodology/approach First, an evaluation model for designer knowledge abilities based on v-SVM is built, which considers the fuzziness and dynamics of designer knowledge abilities. Next, a pre-estimation method for the design time of complex products based on v-SVM is built. This method takes into account the impacts of designer knowledge abilities and design task characteristics on the design time. Then, an adaptive genetic algorithm is programmed to optimize the parameters in the evaluation model and the pre-estimation method. Finally, a practical application and comparative analysis of the proposed pre-estimation method is suggested to verify the validity and applicability of this research. Findings First, the evaluation of designer knowledge abilities is a prediction problem that is both fuzzy and multivariate time series. Second, the pre-estimation of design time is a problem that is fuzzy and multivariate. Third, the pre-estimation accuracy of the proposed method is higher when compared with traditional methods. Originality/value This paper presents an intelligent pre-estimation method of design time for complex products. Unlike previous research, the pre-estimation method takes into account the impacts of both the designer knowledge abilities and the design task characteristics on the design time.

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