{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T08:00:17Z","timestamp":1767772817475,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2012,10,15]],"date-time":"2012-10-15T00:00:00Z","timestamp":1350259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Forecasting the unit cost of every product type in a factory is an important task. However, it is not easy to deal with the uncertainty of the unit cost. Fuzzy collaborative forecasting is a very effective treatment of the uncertainty in the distributed environment. This paper presents some linear fuzzy collaborative forecasting models to predict the unit cost of a product. In these models, the experts\u2019 forecasts differ and therefore need to be aggregated through collaboration. According to the experimental results, the effectiveness of forecasting the unit cost was considerably improved through collaboration.<\/jats:p>","DOI":"10.3390\/a5040449","type":"journal-article","created":{"date-parts":[[2012,10,16]],"date-time":"2012-10-16T03:33:50Z","timestamp":1350358430000},"page":"449-468","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Forecasting the Unit Cost of a Product with Some Linear Fuzzy Collaborative Forecasting Models"],"prefix":"10.3390","volume":"5","author":[{"given":"Toly","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung City, 407, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2012,10,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1080\/00207720902974553","article-title":"A fuzzy-neural knowledge-based system for job completion time prediction and internal due date assignment in a wafer fabrication plant","volume":"40","author":"Chen","year":"2009","journal-title":"Int. J. Sys. Sci."},{"key":"ref_2","first-page":"583","article-title":"A hybrid fuzzy and neural approach with virtual experts and partial consensus for DRAM price forecasting","volume":"8","author":"Chen","year":"2012","journal-title":"Int. J. Innov. Comput. Inf. Control"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5830","DOI":"10.1016\/j.eswa.2008.07.058","article-title":"An online collaborative semiconductor yield forecasting system","volume":"36","author":"Chen","year":"2009","journal-title":"Expert Sys. Appl."},{"key":"ref_4","first-page":"201","article-title":"An application of fuzzy collaborative intelligence to unit cost forecasting with partial data access by security consideration","volume":"7","author":"Chen","year":"2011","journal-title":"Int. J. Technol. Intel. Plan."},{"key":"ref_5","first-page":"36","article-title":"Applying a fuzzy and neural approach for forecasting the foreign exchange rate","volume":"1","author":"Chen","year":"2011","journal-title":"Int. J. Fuzzy Sys. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1016\/j.cie.2011.05.007","article-title":"Applying the hybrid fuzzy c means-back propagation network approach to forecast the effective cost per die of a semiconductor product","volume":"61","author":"Chen","year":"2011","journal-title":"Comput. Ind. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Chen, T. (2012). Some linear fuzzy collaborative forecasting models for semiconductor unit cost forecasting. Int. J. of Fuzzy Sys. Appl., in press.","DOI":"10.4018\/ijfsa.2013010102"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1142\/S0218488508005030","article-title":"A fuzzy-neural system incorporating unequally important expert opinions for semiconductor yield forecasting","volume":"16","author":"Chen","year":"2008","journal-title":"Int. J. Uncertain. Fuzziness Knowl. Based Syst."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Chen, T., Lin, C.W., and Wang, Y.C. (2012). A fuzzy collaborative forecasting approach for WIP level estimation in a wafer fabrication factory. Appl. Math. Inf. Sci., in press.","DOI":"10.12785\/amis\/070427"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"763","DOI":"10.3233\/IDA-2011-0494","article-title":"A fuzzy-neural approach for global CO2 concentration forecasting","volume":"15","author":"Chen","year":"2011","journal-title":"Intel. Data Anal."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/s00170-010-2712-5","article-title":"A hybrid fuzzy and neural approach for forecasting the book-to-bill ratio in the semiconductor manufacturing industry","volume":"54","author":"Chen","year":"2011","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/978-3-540-68860-0_6","article-title":"Collaborative architectures of fuzzy modeling","volume":"5050","author":"Pedrycz","year":"2008","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1016\/S0167-8655(02)00130-7","article-title":"Collaborative fuzzy clustering","volume":"23","author":"Pedrycz","year":"2002","journal-title":"Pattern Recognit. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1062","DOI":"10.1109\/TSMCB.2008.925728","article-title":"A multifaceted perspective at data analysis: A study in collaborative intelligent agents","volume":"38","author":"Pedrycz","year":"2008","journal-title":"IEEE Trans. Syst., Man. Cybern., Part B: Cybern."},{"key":"ref_15","unstructured":"Carnes, R. (1991, January 20-22). Long-term cost of ownership: beyond purchase price. Proceedings of 1991 IEEE\/SEMI International Semiconductor Science Symposium, Burlingame, CA, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/66.554493","article-title":"Cost and cycle time performance of fabs based on integrated single-wafer processing","volume":"10","author":"Wood","year":"1997","journal-title":"IEEE Trans. Semi. Manuf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/S0167-9317(00)00504-9","article-title":"Cost reduction strategies for wafer expenditure","volume":"56","author":"Pfitzner","year":"2001","journal-title":"Microelectr. Eng."},{"key":"ref_18","first-page":"93","article-title":"Infused design I. Theory","volume":"15","author":"Shai","year":"2004","journal-title":"Res. Eng. Design Res."},{"key":"ref_19","first-page":"108","article-title":"Infused design II. Practice","volume":"15","author":"Shai","year":"2004","journal-title":"Res. Eng. Design Res."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"B\u00fcy\u00fck\u00f6zkan, G., and Vardaloglu, Z. (2009, January 6\u20138). Analyzing of Collaborative Planning, Forecasting and Replenishment Approachusing Fuzzy Cognitive Map. Proceeding of 2009 International Conference on Computers and Industrial Engineering, University of Technology of Troyes, France.","DOI":"10.1109\/ICCIE.2009.5223521"},{"key":"ref_21","first-page":"412","article-title":"Analyzing CPFR supporting factors with fuzzy cognitive map approach","volume":"31","author":"Feyzioglu","year":"2009","journal-title":"World Academy Sci. Eng. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1108\/17410380810869941","article-title":"Collaborative forecasting in networked manufacturing enterprises","volume":"19","author":"Poler","year":"2008","journal-title":"J. Manuf. Technol. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s00163-011-0114-9","article-title":"Fuzzy modelling of consensus during design conflict resolution","volume":"23(1)","author":"Ostrosi","year":"2012","journal-title":"Res. Eng. Design"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.cie.2011.07.002","article-title":"A collaborative demand forecasting process with event-based fuzzy judgements","volume":"61","author":"Cheikhrouhou","year":"2011","journal-title":"Comput. Ind. Eng."},{"key":"ref_25","unstructured":"Gruber, H. (1994). Learning and Strategic Product Innovation: Theory and Evidence for the Semiconductor Industry, Elsevier."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/S1568-4946(02)00066-2","article-title":"A fuzzy back propagation network for output time prediction in a wafer fab","volume":"2","author":"Chen","year":"2003","journal-title":"Appl. Soft Comput."},{"key":"ref_27","first-page":"373","article-title":"A hybrid fuzzy and neural approach for evaluating the cost competitiveness of a semiconductor product","volume":"6","author":"Chen","year":"2010","journal-title":"Int. J. Technol. Intel. Plan."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1007\/s00170-007-1007-y","article-title":"A SOM-FBPN-ensemble approach with error feedback to adjust classification for wafer-lot completion time prediction","volume":"37","author":"Chen","year":"2008","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1109\/66.762883","article-title":"A fuzzy set approach for yield learning modeling in wafer manufacturing","volume":"12","author":"Chen","year":"1999","journal-title":"IEEE Trans. Semicond. Manuf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/0165-0114(88)90054-1","article-title":"Possibilistic linear systems and their application to the linear regression model","volume":"272","author":"Tanaka","year":"1988","journal-title":"Fuzzy Sets Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/0165-0114(94)90144-9","article-title":"Fuzzy linear regression with fuzzy intervals","volume":"63","author":"Peters","year":"1994","journal-title":"Fuzzy Sets Syst."},{"key":"ref_32","unstructured":"Donoso, S., Marin, N., and Vila, M.A. (2006, January 28\u201330). Quadratic programming models for fuzzy regression. Proceedings of International Conference on Mathematical and Statistical Modeling in Honor of Enrique Castillo, Ciudad Real, Spain."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.mcm.2006.04.014","article-title":"Parameterized defuzzification with maximum entropy weighting function\u2014another view of the weighting function expectation method","volume":"45","author":"Liu","year":"2007","journal-title":"Math. Com. Mod."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Eraslan, E. (2009). The estimation of product standard time by artificial neural networks in the molding industry. Math. Probl. Eng., article ID 527452.","DOI":"10.1155\/2009\/527452"}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/5\/4\/449\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:52:48Z","timestamp":1760219568000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/5\/4\/449"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,10,15]]},"references-count":34,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2012,12]]}},"alternative-id":["a5040449"],"URL":"https:\/\/doi.org\/10.3390\/a5040449","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2012,10,15]]}}}