Selecting A Sports Car Through Data Mining of Critical Features

被引:0
|
作者
Khan, Sharjeel Ali [1 ]
Manarvi, Irfan [2 ]
机构
[1] Iqra Univ, Dept Management Sci, Iqra, Pakistan
[2] IHITECH Univ, Taxila, Pakistan
关键词
Sports car selection; Data mining; Performance evaluation of automotive; Information for sports cars selection; Brake horsepower; Top speed;
D O I
10.1109/ICCIE.2009.5223721
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Sports cars enthusiasts are always on a look out for the best mix of performance and price parameters for selection of their dream cars. They normally wish to enjoy the rush of adrenaline at top speeds and aspire to have most economic solutions for their selection. Their decision making process gets seriously hampered when sports cars manufacturers are unable to meet best choices at acceptable prices. Advances in technologies add to problems of designers and enhance expectations of buyers to receive even better features in cars. The overall problem is seen as a difficulty in decision making both for buyers and automakers. A host of marketing companies and media managers are involved in launching advertising campaigns for these cars which further aggravates the problems of decision making in sports car selection. This research was focused on providing a methodology of selecting a car by analyzing the data available for various critical parameters such as price, top speed, engine size and brake horsepower information to buyers for making optimum choices. Data of over 100 different makes of sports cars was collected for these parameters. It was then analyzed to arrive at possible choices a buyer could make on the basis of his/her preferred criteria. A total of 5 cars were shortlisted as the best possible choices considering these parameters.
引用
收藏
页码:1480 / +
页数:2
相关论文
共 50 条
  • [31] Apriori algorithm for economic data mining in sports industry
    Xiang, Yaguang, 1600, Transport and Telecommunication Institute, Lomonosova street 1, Riga, LV-1019, Latvia (18):
  • [32] Business Intelligence in Sports Retail: Data Mining Application
    Castelo-Branco, Francisca
    Reis, Jose Luis
    Vieira, Jose Carvalho
    Marques dos Santos, Jose Paulo
    PROCEEDINGS OF 2021 16TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2021), 2021,
  • [33] Critical Feature Selection and Critical Sampling for Data Mining
    Ribeiro, Bernardete
    Silva, Jose
    Sung, Andrew H.
    Suryakumar, Divya
    COMPUTATIONAL INTELLIGENCE, CYBER SECURITY AND COMPUTATIONAL MODELS: MODELS AND TECHNIQUES FOR INTELLIGENT SYSTEMS AND AUTOMATION, 2018, 844 : 13 - 24
  • [34] Mining gene expression data using data mining techniques : A critical review
    Mabu, Audu Musa
    Prasad, Rajesh
    Yadav, Raghav
    JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 2020, 41 (03): : 723 - 742
  • [35] Learning through data mining
    Zalik, KR
    COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, 2005, 13 (01) : 60 - 65
  • [36] New data and features for advanced data mining in Manteia
    Tassy, Olivier
    NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) : D707 - D711
  • [37] Mining of Classification Patterns in Clinical Data through Data Mining Algorithms
    Jacob, Shomona Gracia
    Ramani, R. Geetha
    PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI'12), 2012, : 997 - 1003
  • [38] Data Currency Assessment Through Data Mining
    Pio Alvarez, Sergio
    Marotta, Adriana
    Tansini, Libertad
    ADVANCES IN CONCEPTUAL MODELING, ER 2015 WORKSHOPS, 2015, 9382 : 273 - 282
  • [39] Data Acquisition and Mining Algorithm of Car Networking under Big Data Background
    Xiong, Guohua
    INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING, 2019, 15 (01) : 4 - 17
  • [40] Design of a sports culture data fusion system based on a data mining algorithm
    Lan Zhang
    Personal and Ubiquitous Computing, 2020, 24 : 75 - 86