臺灣博碩士論文加值系統

隨著高科技時代的來臨，通訊科技業呈現蓬勃發展；為滿足消費者不同的需求，手機已從最基本的語音通話功能演變到現在可以聽音樂、上網、玩遊戲，甚至像電腦一樣能自行安裝軟體。智慧型手機即是上述需求下的產物，而作業系統就像是智慧型手機的心臟，它會影響整體的執行效率以及使用者的操作偏好，因此智慧型手機作業系統的選擇變成一個重要的課題。在評選作業系統時，需要考量許多準則。有些準則是可量化的，如應用程式數量；有些是質化的，如安全性。而且對於不同的決策者來說，準則間的重要性也會有不同的看法。當評估的資料具有模糊或質化特性時，模糊多準則決策能夠有效的結合量化準則與質化準則，進行綜合評量分析。
本研究即以模糊多準則決策來建構一個智慧型手機作業系統的評選模式，模式可同時考量質化與量化準則以及不同準則間的重要性。模式所得最後模糊評估值之歸屬函數可推導求出，並在應用 Chen (1985)的最大集與最小集觀念發展最大面積與最小面積比序法來求解模糊值，再依照總面積大小來作各候選作業系統的排序，以選出最附合決策者的智慧型手機作業系統。最後再以數值例子來驗證所建模式之可行性。

The market share of Smart phone has been increasing. The operating system (OS) is just like the heart of smart phone. OS influences the efficiency of overall operation and user preferences of smart phone. Thus the selection of the OS of smart phone has then become a very important issue.
Many criteria must be considered when evaluating an OS of smart phone. Some criteria are quantitative, such as the numbers of applications; some are qualitative, such as, the security of the OS. Furthermore, different decision maker may have different opinion on the different importance among criteria. The purpose of this research is to suggest a fuzzy MCDM model for the evaluation and selection of the OS of smart phone. The membership functions of the final fuzzy evaluation values in the model will be derived. A ranking approach of maximizing area and minimizing area is suggested to produce the defuzzification values in order to obtain the ranking of the alternatives. Finally, a numerical example demonstrates the feasibility of the proposed model.

ACKNOWLEDGEMENTS I
ABSTRACT II
TABLE OF CONTENTS III
LIST OF TABLES VI
LIST OF FIGURES VIII
CHAPTER ONE INTRODUCTION 1
1.1 Background and Motivation 1
1.2 Problem Identification 3
1.3 Research Objectives 4
1.4 Research Framework 4
CHAPTER TWO LITERATURE REVIEW 7
2.1 Definition of Phones 8
2.1.1Feature Phones 8
2.1.2 Smart Phone 9
2.2 Smart Phone System 12
2.2.1What is a System 12
2.2.2 Situation and Development of Smart Phone System 13
2.2.3 The Introduction of Smart Phone Operating Systems 16
2.3 Related Works on Smart Phone Operating Systems 22
2.4 Related Works on Fuzzy Multi-Criteria Decision Making Method 25
2.5 Fuzzy Number Ranking 27
2.6 Criteria Assessment 30
CHAPTER THREE FUZZY SET THEORY 33
3.1 Fuzzy Set 33
3.2 Fuzzy Numbers 33
3.3 α-Cut 34
3.4 Arithmetic Operations on Fuzzy Numbers 35
3.5 Linguistic Variable 35
CHAPTER FOUR MODEL ESTABLISHMENT 37
4.1 Aggregate Ratings of Alternatives versus Qualitative Criteria 37
4.2 Normalize Values of Alternatives versus Quantitative Criteria 38
4.3 Average Importance Weights 38
4.4 Aggreagte the Ratings and Weights 39
4.5 Rank Fuzzy Numbers 42
CHAPTER FIVE NUMERICAL EXAMPLE 47
5.1 Ratings of Alternatives versus Qualitative Criteria 49
5.3 Averaged Weights of Criteria 53
5.4 Development of Membership Function 55
5.5 Defuzzification Values 59
CHAPTER SIX CONCLUSIONS 60
6.1 Conclusions 60
6.2 Suggestions for Future Research 61
REFERENCES 63
APPENDIX A 68
APPENDIX B 70

Abbasbandy, S. & Hajjari, T. (2009). A new approach for ranking of trapezoidal fuzzy numbers. Computers and Mathematics with Applications, 57, 413-419.
Abowd, G.D., Iftode, L. & Mitchell, H. (2005). The smart phone: a first platform for pervasive computing. Pervasive Computing, 4, 18-19.
Asady, B. (2009). The revised method of ranking LR fuzzy number based on deviation degree. Expert Systems with Applications, 37, 5056-5060.
Ballagas, R., Borchers, J., Rohs, M. & Sheridan, J.G. (2006). The smart phone: a ubiquitous input device. Pervasive Computing, 5, 70-77.
Bellman, R. E. & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17, 141-164.
Buchanan, M. (2008). Illustrated guide to smartphone OSes. Gizmodo. http://gizmodo.com/5061086/giz-explains-illustrated-guide-to-smartphone-oses.
Carlsson, C. & Fullér, R. (1996). Fuzzy multiple critera decision making: Recent development. Fuzzy Sets and Systems, 78, 139-153.
Chang, T. H. & Wang, T.C. (2009). Using the fuzzy multi-criteria decision making approach for measuring the possibility of successful knowledge management. Information Sciences, 179, 355-370.
Chen, C.S. (2007). The study of consumer behaviors of smartphone－based on bussiness people. Master's thesis, Ming Chuan University.
Chen, C.T. (2009). A Competitive analysis of the smartphone industry. Master's thesis, National Taiwan University.
Chen, S.H. (1985). Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets and Systems, 17, 113-129.
Chen, S. J. & Hwang, C.L. (1992). Fuzzy Multiple Attribute Decision Making Method and Application. New York：Spring-Verlag.
Cheng, C. H. (1998). A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets and Systems, 95, 307-317.
Cho, Y.C. & Jeon, J.W. (2007). Current software platforms on mobile phone. Automation and Systems, 1862-1867.
Chou, C. C. (2007). A fuzzy MCDM method for solving marine transshipment container port selection problems. Applied Mathematics and Computation, 186, 435-444.
Coustan, D. & Strickland. J. (2007). How smartphones work. Howstuffworks. http://communication.howstuffworks.com/smartphone2.htm.
Covert, A. (2009). What makes the five smartphone platforms different. Gizmodo. http://gizmodo.com/5173865/giz-explains-what-makes-the-five-smartphone-platforms-different.
Elena, M. (2007). Analysis: how smartphone platforms compare. InformationWeek. http://www.informationweek.com/news/personal_tech/showArticle.jhtml?articleID=196902226&pgno=1&queryText=&isPrev=.
Farhadinia, B. (2009). Ranking fuzzy numbers based on lexicographical ordering. Applied Mathematics and Computer Sciences, 5(4), 248-251.
Foresman, C. (2009). iPhone and android in two-horse smartphone OS race. Ars technica.http://arstechnica.com/apple/news/2009/11/admob-iphone-and-android-in -two-horse-smartphone-os-race.ars.
Jakajima. (2008). White Paper An innovative tool to benchmark Smartphone Operating Systems. Netherland: Jakajima BV.
JDPOWER. (2010). Wireless consumer smartphone and traditional mobile phone satisfaction. JDPOWER. http://businesscenter.jdpower.com/news/pressrelease
.aspx?ID=2010039.
Kaufmann, A. & Gupta, M.M. (1991). Introduction to fuzzy arithmetic-theory and application. New York : Van Nostrand Reinhold.

Keijzers, J., Ouden, E. & Lu, Y. (2008). Usability benchmark study of commercially available smart phones: cell phone type platform, PDA type platform and PC type platform. International Conference of Human Computer Interaction with Mobile Devices and Services, 265-272.
Lin, C.R. (2005). Consuming research of buying behavior of electronic product：take smart phone as an example. Master's thesis, DAYEH University.
Lin, M.H. (2002). The impact of consumer knowledge on mobile-phone purchase decisions. Master's thesis, National Dong Hwa University.
Liou, T.S. & Wang, M.J. (1992). Fuzzy weighted average: an improved algorithm. Fuzzy Sets and Systems. 49, 307–15.
Malykhina, E. (2007). Analysis: how smartphone platforms compare. InformationWeek.http://www.informationweek.com/news/personal_tech/showArticle.jhtml?articleID=196902226
Marcus, A. & Chen. E. (2002). Designing the PDA of the future. International Conference of Interactions. 9, 34-44.
Pash, A. (2009). Remains of the day: smartphone cost of ownership edition. Lifehacker.http://lifehacker.com/5393028/remains-of-the-day-smartphone-cost-of-ownership-edition.
Perez, S. (2010). The truth about mobile application stores. ReadWtiteWeb. http://www.readwriteweb.com/archives/the_truth_about_mobile_application_stores.php.
Silver, S. (2009). Apple, rim outsmart phone market. THE WALL STREET JOURNAL.http://online.wsj.com/article/SB124805149501664033.html#mod=loomia?loomia_si=t0:a16:g4:r1:c0:b0.
Su, Y.J. (2009). Consumer preferences for smart phones. Master's thesis, National Chiao Tung University.
Vaughan-Nichols, S.J. (2003). OSs battle in the smart-phone market. Computer, 36, 10-12.
Wang, Y.J. & Lee, H.S. (2008). The revised method of ranking fuzzy numbers with an area between the centroid and original points. Computers & Mathematics with Applications, 55, 2033-2042.
Yang, Y.T. (2009). The development trend analysis of smart phone industry. Master's thesis, National Cheng Kung University.
Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8, 338-353.
Zadeh, L.A. (1975). Fuzzy logic and approximate reasoning. Synthese, 30, 407-428.