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基于灰色多元变权组合预测模型对山东省海水养殖产量预测
王艳明, 郭云水, 王锐
山东工商学院
摘要:
为了进一步提高海水养殖产量预测精度,考虑多因素对海水养殖产量的影响,文章基于变权组合预测模型,充分结合长短期记忆(Long Short-Term Memory, LSTM)神经网络预测模型、GM(1,N)预测模型和偏最小二乘回归预测模型等传统统计预测模型的优点,构建出一种基于灰色多元变权组合预测模型,并对山东省海水养殖总产量和分类产量进行了预测。实证结果显示,基于灰色多元变权组合预测模型对山东省海水养殖产量的预测精度高达99.13%,预测精度显著优于LSTM神经网络等各单项模型,并能综合于LSTM神经网络、GM(1,N)预测模型和偏最小二乘回归预测模型的优点,弥补各单项模型的不足,提高预测精度和可靠性。根据预测结果,到2025年山东省海水养殖产量仍将保持良好发展,海水养殖产量将达到579.28万吨,平均增长速度为3.11%,而鱼类、甲壳类、贝类、藻类以及海参海水养殖产量将分别达到6.27万吨、26.27万吨、445.83万吨、68.65万吨和9.57万吨。
关键词:  海水养殖  LSTM神经网络  变权组合预测
DOI:
分类号:S968;TP183 ?
基金项目:国家社会科学基金重点项目:“中国海洋经济大数据监测体系设计与应用研究”(21ATJ006)
Prediction of Mariculture Production in Shandong Province Based on Grey Multiple Variable Weight Combination Prediction Model
WANG Yanming, GUO Yun-shui, WANG Rui
Shandong Technology and Business University
Abstract:
In order to further improve the accuracy of seawater aquaculture yield prediction and consider the impact of multiple factors on seawater aquaculture yield, this article is based on a variable weight combination prediction model, fully combining the advantages of traditional statistical prediction models such as Long Short Term Memory (LSTM) neural network prediction model, GM (1, N) prediction model, and partial least squares regression prediction model, and constructing a grey multiple variable weight combination prediction model, And the total and classified yields of seawater aquaculture in Shandong Province were predicted. The empirical results show that the prediction accuracy of the grey multiple variable weight combination prediction model for seawater aquaculture production in Shandong Province is as high as 99.13%, which is significantly superior to various single item models such as LSTM neural network. It can also integrate the advantages of LSTM neural network, GM (1, N) prediction model, and partial least squares regression prediction model, make up for the shortcomings of each single item model, and improve prediction accuracy and reliability. According to the predicted results, the production of marine aquaculture in Shandong Province will still maintain good development by 2025, reaching 5.7928 million tons, with an average growth rate of 3.11%. The production of fish, crustaceans, shellfish, algae, and sea cucumber in marine aquaculture will reach 62700 tons, 262700 tons, 4.4583 million tons, 686500 tons, and 95700 tons, respectively.
Key words:  Mariculture, LSTM neural network, Variable weight combination prediction
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