Honghong Wang¹, Zhixin Xiong^1,*, Yunchao Hu¹, Zhijian Liu¹, Long Liang²

Journal of Renewable Materials, Vol.11, No.6, pp. 2713-2727, 2023, DOI:10.32604/jrm.2023.025817 - 27 April 2023

Abstract This study aims to realize the sharing of near-infrared analysis models of lignin and holocellulose content in pulp wood on two different batches of spectrometers and proposes a combined algorithm of SPA-DS, MCUVE-DS and SiPLS-DS. The Successive Projection Algorithm (SPA), the Monte-Carlo of Uninformative Variable Elimination (MCUVE) and the Synergy Interval Partial Least Squares (SiPLS) algorithms are respectively used to reduce the adverse effects of redundant information in the transmission process of the full spectrum DS algorithm model. These three algorithms can improve model transfer accuracy and efficiency and reduce the manpower and material consumption… More >

Ping-Huan Kuo^1,2, Sing-Yan Chen¹, Her-Terng Yau^1,2,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1577-1596, 2023, DOI:10.32604/csse.2023.036292 - 09 February 2023

Abstract Cars are regarded as an indispensable means of transportation in Taiwan. Several studies have indicated that the automotive industry has witnessed remarkable advances and that the market of used cars has rapidly expanded. In this study, a price prediction system for used BMW cars was developed. Nine parameters of used cars, including their model, registration year, and transmission style, were analyzed. The data obtained were then divided into three subsets. The first subset was used to compare the results of each algorithm. The predicted values produced by the two algorithms with the most satisfactory results… More >

Panyu Liu¹, Huilin Ren², Xiaojun Shi³, Yangyang Li^{4, *}, Zhiping Cai¹, Fang Liu⁵, Huacheng Zeng⁶

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2321-2334, 2020, DOI:10.32604/cmc.2020.010522 - 16 September 2020

Abstract Deep learning technology has been widely used in computer vision, speech recognition, natural language processing, and other related fields. The deep learning algorithm has high precision and high reliability. However, the lack of resources in the edge terminal equipment makes it difficult to run deep learning algorithms that require more memory and computing power. In this paper, we propose MoTransFrame, a general model processing framework for deep learning models. Instead of designing a model compression algorithm with a high compression ratio, MoTransFrame can transplant popular convolutional neural networks models to resources-starved edge devices promptly and More >