• Title/Summary/Keyword: Compensation by prediction error

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Prediction of movie audience numbers using hybrid model combining GLS and Bass models (GLS와 Bass 모형을 결합한 하이브리드 모형을 이용한 영화 관객 수 예측)

  • Kim, Bokyung;Lim, Changwon
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.447-461
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    • 2018
  • Domestic film industry sales are increasing every year. Theaters are the primary sales channels for movies and the number of audiences using the theater affects additional selling rights. Therefore, the number of audiences using the theater is an important factor directly linked to movie industry sales. In this paper we consider a hybrid model that combines a multiple linear regression model and the Bass model to predict the audience numbers for a specific day. By combining the two models, the predictive value of the regression analysis was corrected to that of the Bass model. In the analysis, three films with different release dates were used. All subset regression method is used to generate all possible combinations and 5-fold cross validation to estimate the model 5 times. In this case, the predicted value is obtained from the model with the smallest root mean square error and then combined with the predicted value of the Bass model to obtain the final predicted value. With the existence of past data, it was confirmed that the weight of the Bass model increases and the compensation is added to the predicted value.

A Study on the Interframe Image Coding Using Motion Compensated and Classified Vector Quantizer (Ⅰ: Theory and Computer Simulation) (이동 보상과 분류 벡터 양자화기를 이용한 영상 부호화에 관한 연구 (Ⅰ: 이론및 모의실험))

  • Kim, Joong-Nam;Choi, Sung-Nam;Park, Kyu-Tae
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.3
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    • pp.13-20
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    • 1990
  • This paper describes an interframe image coding using motion compensated and classified vector quantizer (MC-CVQ). It is essential to carefully encode blocks with significant pels in motion compensated vector quantizers (MCVQ). In this respect, we propose a new CVQ algorithm which is appropriate to the coding of interframe prediction error after motion compensation. In order to encode an image efficiently at a low bit rate, we partition each block, which is the processing element in MC, into equally sized 4 vectors, and classify vectors into 15 classes according to the position of significant pels. Vectors in each class are then encoded by the vector quantizer with the codebook independently designed for the class. The computer simulation shows that the signal-to-noise ratio and the average bit rate of MC-CVQ are 35-37dB and 0.2-0.25bit/pel, respectively, for the videophone or video conference type image.

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