The Application Of Naive Bayesian Classification Algorithm In Notebook Computer ODM Industry

With its portability, efficiency and flexibility, notebook computer has become anecessity in our daily life of modern people since90's. Competition within notebookcomputer original design manufacturers (ODM) becomes much keener owing to thefact that the requirement of user on update speed, stability and price are constantlyincreasing. New technological platforms allow notebook computer designer andmanufacturers update their product on a monthly basis and thus making high speed,high efficiency and profit maximization the keys for survival. Quick response, highproductivity, reliable quality and logistics and low cost are the necessary conditionsfor notebook computer ODMs' development. Assuring the launch plan of largequantities of notebook computers with high quality and reasonable price is always alesson for the notebook ODMs.With the practical requirement from the notebook computer ODMs,we haveconducted a study on one notebook computer ODM. Based on the related workingexperience in the industry and data information which are related with daily notebookcomputer manufacturing and operation, we have preliminarily concluded that themajor factors which affects the productivities of manufacturers are: human-related,manufacturing planning and device-related ones.Based on this assumption, this thesis demonstrates the experimental analysis andvalidation research with the use of data from notebook computer ODMs and NaiveBayesian classification algorithm. The results shown in this thesis can be used toassist notebook computer ODMs to make manufacturing resource allocation and helpenterprises to make more reasonable, precise and scientific regulations formanufacturing and operation, thus maximizing the profit of enterprises and winningmore clients and orders. The major work of the project demonstrated in this thesis includes:(1) Sorting out the manufacturing flow in the notebook ODMs, and makingassumptions on the factors which affect the productivity.(2) Studying algorithms of pattern recognition and its included Naive Bayesianalgorithms.(3) Implementation of a system based on Naive Bayesian algorithm, and thedetailed explanation of using training data and execution of the application.The evaluation of the algorithm and the finding of the real factors whichaffect the productivity of notebook computers.(4) A summary on the use of Naive Bayesian algorithm and its effect on theproductivity, a validation of the algorithm.The experimental results prove the assumption raised, and also shows theeffectiveness of using this algorithm for analyzing the productivity of notebookcomputer ODMs.