井冈山大学学报（自然科学版）Issue(5)：29-32,4.DOI:10.3969/j.issn.1674-8085.2014.05.007
食品比热容的支持向量回归预测
SUPPORT VECTOR REGRESSION PREDICTION OF THE SPECIFIC HEAT CAPACITY OF FOOD
摘要
Abstract
The dependence model of specific heat capacity on the contents of water, protein, carbohydrate and fat for different foods was established using the particle swarm optimization algorithm and support vector regression approach. Furthermore, the prediction precision of the dependence model is higher than that of back propagation neural network for the same training and test samples. Its generalization ability is also stronger than that of back propagation neural network. The experiment and analysis shows that the dependence model can be used to effectively estimating the specific heat capacity of food.关键词
食品/比热容/支持向量回归/粒子群算法/预测Key words
food/specific heat capacity/support vector regression/particle swarm optimization/prediction分类
信息技术与安全科学引用本文复制引用
温玉锋,陈志铨,汤鹏杰,赖章丽..食品比热容的支持向量回归预测[J].井冈山大学学报（自然科学版）,2014,(5):29-32,4.基金项目
国家自然科学基金项目(11347210) （11347210）
