A Sales Forecasting Model in Automotive Industry using Adaptive Neuro-Fuzzy Inference System(Anfis) and Genetic Algorithm(GA)

被引:1
|
作者
Vahabi, Amirmahmood [1 ]
Hosseininia, Shahrooz Seyyedi [2 ]
Alborzi, Mahmood [1 ]
机构
[1] Islamic Azad Univ, Sci & Res Branch, Dept IT Management, Tehran, Iran
[2] Islamic Azad Univ, Karaj Branch, Dept Ind Management, Tehran, Iran
关键词
Sales Forecasting; Adaptive Neuro-fuzzy inference system (Anfis); Genetic Algorithm (GA);
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowadays, Sales Forecasting is vital for any business in competitive atmosphere. For an accurate forecasting, correct variables should be considered. In this paper, we address these problems and a technique is proposed which combines two artificial intelligence algorithms in order to forecast future automobile sales in Saipa group which is a leading Automobile manufacturer in Iran. Anfis is used as the base technique which is combined with GA. GA is used in order to tune the Anfis results. Furthermore, sales forecasting is succeeded with annual data of years between 1990 and 2016. With this in mind, per capita income, inflation rate, housing, Importation, Currency Rate (USD), loan interest rate and automobile import tariffs are selected as effective variables in the proposed model. Finally, we compare our model with ANN model which is a well-known forecasting model.
引用
收藏
页码:24 / 30
页数:7
相关论文
共 50 条
  • [1] Rainfall-runoff modeling using adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA)
    Vakili, Shabnam
    Mousavi, Seyed Morteza
    WATER SUPPLY, 2022, 22 (10) : 7460 - 7475
  • [2] Optimal design of adaptive neuro-fuzzy inference system using genetic algorithm for electricity demand forecasting in Iranian industry
    Shahram Mollaiy-Berneti
    Soft Computing, 2016, 20 : 4897 - 4906
  • [3] Optimal design of adaptive neuro-fuzzy inference system using genetic algorithm for electricity demand forecasting in Iranian industry
    Mollaiy-Berneti, Shahram
    SOFT COMPUTING, 2016, 20 (12) : 4897 - 4906
  • [4] An adaptive neuro-fuzzy inference system (anfis) model for assessing occupational risk in the shipbuilding industry
    Fragiadakis, N. G.
    Tsoukalas, V. D.
    Papazoglou, V. J.
    SAFETY SCIENCE, 2014, 63 : 226 - 235
  • [5] A hybrid of adaptive neuro-fuzzy inference system and genetic algorithm
    Varnamkhasti, M. Jalali
    Hassan, Nasruddin
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2013, 25 (03) : 793 - 796
  • [6] ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) FOR FORECASTING: THE CASE OF THE CZECH STOCK MARKET
    Jankova, Zuzana
    15TH ANNUAL INTERNATIONAL BATA CONFERENCE FOR PH.D. STUDENTS AND YOUNG RESEARCHERS (DOKBAT), 2019, : 457 - 465
  • [7] Forecasting project success in the construction industry using adaptive neuro-fuzzy inference system
    Mavi, Neda Kiani
    Brown, Kerry
    Fulford, Richard
    Goh, Mark
    INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT, 2024, 24 (14) : 1550 - 1568
  • [8] An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM
    Caydas, Ulas
    Hascalik, Ahmet
    Ekici, Sami
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) : 6135 - 6139
  • [9] LANDSLIDE SUSCEPTIBILITY MAPPING BY USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Choi, J.
    Lee, Y. K.
    Lee, M. J.
    Kim, K.
    Park, Y.
    Kim, S.
    Goo, S.
    Cho, M.
    Sim, J.
    Won, J. S.
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1989 - 1992
  • [10] Adaptive Neuro-Fuzzy Inference System for drought forecasting
    Bacanli, Ulker Guner
    Firat, Mahmut
    Dikbas, Fatih
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2009, 23 (08) : 1143 - 1154