Predicting software project effort: A grey relational analysis based method

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.The inherent uncertainty of the software development process presents particular challenges for software effort prediction. We need to systematically address missing data values, outlier detection, feature subset selection and the continuous evolution of predictions as the project unfolds, and all of this in the context of data-starvation and noisy data. However, in this paper, we particularly focus on outlier detection, feature subset selection, and effort prediction at an early stage of a project. We propose a novel approach of using grey relational analysis (GRA) from grey system theory (GST), which is a recently developed system engineering theory based on the uncertainty of small samples. In this work we address some of the theoretical challenges in applying GRA to outlier detection, feature subset selection, and effort prediction, and then evaluate our approach on five publicly available industrial data sets using both stepwise regression and Analogy as benchmarks. The results are very encouraging in the sense of being comparable or better than other machine learning techniques and thus indicate that the method has considerable potential.National Natural Science Foundation of Chin

ANALISIS USABILITY WEBSITE AKADEMIK PERGURUAN TINGGI DI INDONESIA MENGGUNAKAN METODE ELECTREE, GREY RELATIONAL ANALYSIS, DAN WEIGHTED PRODUCT MODEL

Penelitian ini dilakukan untuk menganalisis kualitas usability website akademik perguruan tinggi di Indonesia serta untuk mengetahui pengaruh kualitas usability website terhadap peringkat dalam perankingan Webometrics. Hasil analisis kemudian disajikan dalam bentuk perankingan, menggunakan metode ELECTREE, Grey Relational Analysis, dan Weighted Product Model. Penelitian juga bertujuan untuk mengetahui perbandingan hasil perankingan dari ketiga metode tersebut. Objek penelitian ini adalah lima website akademik universitas negeri di Indonesia, yaitu UNY, UGM, UNDIP, UNAIR, UI. Data yang diperoleh kemudian dilakukan kalkulasi untuk memperoleh hasil penilaian. Hasil penilaian kemudian dibuat ranking menggunakan metode ELECTREE, Grey Relational Analysis, dan Weighted Product Model. Hasil perankingan dari ketiga metode kemudian disbandingkan menggunakan tes Friedman. Masing-masing hasil perankingan dari ketiga metode tersebut juga akan dibandingkan dengan hasil perankingan Webometrics yang dirilis pada bulan Januari 2014 dengan menggunakan tes Spearman. Hasil menunjukkan: (1) Hasil perankingan menggunakan metode ELECTREE, Grey Relational Analysis, dan Weighted Product Model adalah signifikan sama. Terbukti nilai probabilitas uji Friedman sebesar 75, yang notabene lebih besar dari taraf signifikansi sebesar 5%, yaitu 5,99 (2) Perbandingan hasil perankingan metode ELECTREE, Grey Relational Analysis, dan Weighted Product Model dengan hasil perankingan Webometrics adalah signifikan sama. Terbukti nilai probabilitas uji Spearman untuk metode, ELECTREE, dan Grey Relational Analysis sebesar mempunyai nilai 0,400 dan 0,850 untuk weighted product model sebesar 0,200 , yang notabene lebih dari taraf signifikansi sebesar 5%, yaitu (rs> 0,3-36) kecuali metode weighted product model. (3) Kualitas usability berpengaruh terhadap peringkat dalam perankingan Webometrics. Terbukti semakin baik kualitas usability website semakin tinggi peringkat website dalam perankingan Webometrics. Kata kunci: usability website, ELECTREE, Grey Relational Analysis, Weighted Product Model, Webometrics Ranking, website akademik

Gri ilişki analizi ve bulanık analitik hiyerarşi süreci yönteminin HEMA analizinde uygulanması

The purpose of this study is to compare three different methods for prioritizing failure modes in a design FMEA study. These methods are traditional approach, Grey Relational Analysis (GRA- under the assumption of risk factors having equal weights) and integration of Grey Relational Analysis and Fuzzy Analytic Hierarchy Process (FAHP) -to estimate weights for the risk factors-. According to the findings, integration of Grey Relational Analysis and fuzzy AHP revealed a difference in prioritizing failure modes from the methods with the assumption of equal weights. Because this method eliminates some of the shortcomings of the traditional approach, it is a useful tool in identifying the high-priority failure modes.Bu çalışmanın amacı bir tasarım HMEA uygulamasında, hata türlerini önceliklendirmede kullanılabilecek üç farklı yöntemi karşılaştırmaktır. Bu yöntemler; geleneksel HMEA risk öncelik sıralaması, Gri İlişki Analizi (risk faktörlerinin ağırlıklarının eşit olduğu varsayımı altında) ve risk faktörlerine farklı ağırlıklar vermek üzere Gri İlişki Analizi ve Bulanık Analitik Hiyerarşi Prosesi (BAHP) yöntemlerinin birlikte uygulanmasıdır. Elde edilen bulgulara göre Gri İlişki Analizi ve bulanık AHP birlikte kullanıldığında oluşan sıralamanın, ağırlıkların eşit olduğu varsayımına dayanan sıralamaya göre farklı olduğu gözlemlenmiştir. Bu yöntemin, geleneksel yaklaşımın bazı sakıncalarını giderebildiği için, öncelikli hata türlerini belirlemede etkin bir yöntem olduğu öne sürülebilir

Multi-objective optimization in WEDM of D3 tool steel using integrated approach of Taguchi method & Grey relational analysis

In this paper, wire electrical discharge machining of D3 tool steel is studied. Influence of pulse-on time, pulse-off time, peak current and wire speed are investigated for MRR, dimensional deviation, gap current and machining time, during intricate machining of D3 tool steel. Taguchi method is used for single characteristics optimization and to optimize all four process parameters simultaneously, Grey relational analysis (GRA) is employed along with Taguchi method. Through GRA, grey relational grade is used as a performance index to determine the optimal setting of process parameters for multiobjective characteristics. Analysis of variance (ANOVA) shows that the peak current is the most significant parameters affecting on multi-objective characteristics. Confirmatory results, proves the potential of GRA to optimize process parameters successfully for multi-objective characteristics

Pitting damage levels estimation for planetary gear sets based on model simulation and grey relational analysis

The planetary gearbox is a critical mechanism in helicopter transmission systems. Tooth failures in planetary gear sets will cause great risk to helicopter operations. A gear pitting damage level estimation methodology has been devised in this paper by integrating a physical model for simulation signal generation, a three-step statistic algorithm for feature selection and damage level estimation for grey relational analysis. The proposed method was calibrated firstly with fault seeded test data and then validated with the data of other tests from a planetary gear set. The estimation results of test data coincide with the actual test records, showing the effectiveness and accuracy of the method in providing a novel way to model based methods and feature selection and weighting methods for more accurate health monitoring and condition prediction

Penerapan Metode Taguchi untuk Kasus Multirespon Menggunakan Pendekatan Grey Relational Analysis dan Principal Component Analysis (Studi Kasus Proses Freis Komposit Gfrp)

Taguchi method is a method for quality control of product by off line. Taguchi method usually used to solve optimization problem with single respon. Multirespon case was done by using Grey Relational Analyisis (GRA) and Principal Component Analysis (PCA). With GRA method is obtained many Grey Relational Grade value. For weight is estimated using PCA. The case study use freis process GFRP composite with characteristic smaller is better. From the research is obtained combination in optimal canditions for factor fiber orientation angle at 150, helix angle at 250, and feed rate at 0,04 mm/rev. While the respon that observed are surface roughness, machine force, and delamination factor. The value of contribution percentage for each factor is 69,596% for fiber orientation angle, 9,768% for helix angle and 11,9841% for feed rate.

A particle swarm optimisation-based Grey prediction model for thermal error compensation on CNC machine tools

Thermal errors can have a significant effect on CNC machine tool accuracy. The thermal error compensation system has become a cost-effective method of improving machine tool accuracy in recent years. In the presented paper, the Grey relational analysis (GRA) was employed to obtain the similarity degrees between fixed temperature sensors and the thermal response of the CNC machine tool structure. Subsequently, a new Grey model with convolution integral GMC(1, N) is used to design a thermal prediction model. To improve the accuracy of the proposed model, the generation coefficients of GMC(1, N) are calibrated using an adaptive Particle Swarm Optimisation (PSO) algorithm. The results demonstrate good agreement between the experimental and predicted thermal error. Finally, the capabilities and the limitations of the model for thermal error compensation have been discussed. Keywords: CNC machine tool, Thermal error modelling, ANFIS, Fuzzy logic, Grey system theory

Optimization of EDM Injection Flushing Type Control Parameters Using Grey Relational Analysis on AISI 304 Stainless Steel Workpiece

This paper deals with optimization of Electrical Discharge Machining (EDM) Injection flushing type control parameters on multi-performance optimization characteristics instead of single performance optimization using Grey Relational Analysis (GRA) Method. The experimental control parameters were being optimized according to their various machining characteristics namely material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR) using copper as the tool and AISI 304 stainless steel as the workpiece. This parameters optimization was based on Taguchi’s orthogonal array (OA) combined with GRA. A grey relational grade (GRG) calculated based on GRA was used to optimize the EDM process with multiple performance characteristics and Taguchi’s L18 OA was used to plan the experiments. The machining parameters selected are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. Results shown that machining performance was improved effectively using this approach. The predicted responses at optimum parameter levels are in good agreement with the results of confirmation experiments conducted for verification tests

Optimization of feed force, tangential force and surface roughness by using grey based Taguchi method

This study investigated the optimization of turning process parameters such as cutting speed, feed rate and depth of cut on EN-19 material using the Grey Relational Analysis (GRA) method. Twenty seven experimental runs based on an orthogonal array of Taguchi method were performed. The feed force (F X), tangential force (FY) and surface roughness (R a) were selected as the quality targets. An optimal parameter combination of the turning operation was obtained using GRA. By analyzing the grey relational grade matrix, the degree of influenced for each controllable process factor onto individual quality targets can be found. The depth of cut is identified to be the most influence on feed force and tangential force, and feed rate is the most influential factor to the surface roughness. Additionally, the analysis of variance (ANOVA) was also applied to identify the most significant factor; the depth of cut is the most significant controlled factor for the turning operation according to the weighted sum grade of the feed force, tangential force and surface roughness

Optimasi Parameter Mesin Laser Cutting Terhadap Kekasaran Dan Laju Pemotongan Pada Sus 316l Menggunakan Taguchi Grey Relational Analysis Method

Parameter optimization is used in manufacturing as an indicator to produce the best manufacturing product. This paper studies an optimization parameters of CNC laser cutting such as focus of laser beam, pressure cutting gases and cutting speed for reducing variation of surface roughness and cutting rate on material SUS 316L. Based on L9(34) orthogonal array parameters, it is analized using ANOVA based on Taguchi method. In order to optimaze the minimum surface roughness and maximum cutting rate in laser cutting process, it is used Grey relational analysis. The confirmation experiments used to validate the optimal results that has done by Taguchi method. The results show that the Taguchi Grey relational analysis is being effective to optimize the machining parameters for laser cutting process with two responses