GA-BP神经网络预测组合模型的构建与全球气温预测OA
Construction of GA-BP Neural Network Prediction Combination Model and Global Temperature Prediction
构建GA-BP神经网络预测组合模型(GBSM),对全球气温进行预测.GBSM模型改进了轮盘赌法,增加了算法的收敛性,选择了适应度比较大的遗传染色体.实验结果表明,GBSM具有精度高、稳定性好等优点,有效提高了预测的精度.未来气温呈"先快后缓"上升趋势:2030年前年均升温约0.25℃,2030-2060年升温速率放缓,2100年较工业化前升高约2.0℃,难破20℃阈值.
A GA-BP neural network prediction combination model(GBSM)was constructed to forecast global temperature.The GBSM model improved the roulette wheel method,enhanced the convergence of the algorithm,and selected the genetic chromosomes with higher fitness.Experimental results showed that GBSM had advantages such as high accuracy and good stability,effectively improving the prediction accuracy.The future temperature trend is expected to rise"rapidly at first and then slowly":the annual average temperature will increase by about 0.25℃ before 2030,and the rate of temperature rise will slow down from 2030 to 2060.By 2100,the temperature will be about 2.0℃ higher than before industrialization,and it is difficult to break the 20℃ threshold.
袁炜;胡艳丽;葛正;章俊杰
淮南师范学院机械与电气工程学院,安徽淮南 232038淮南师范学院机械与电气工程学院,安徽淮南 232038淮南师范学院机械与电气工程学院,安徽淮南 232038淮南师范学院机械与电气工程学院,安徽淮南 232038
天文与地球科学
GA-BP神经网络气温预测改进型轮盘赌
GA-BP neural networktemperature forecastingimproved roulettestability
《牡丹江师范学院学报（自然科学版）》 2026 (2)
24-29,6
安徽省"六卓越一拔尖"项目(2024zybj039)2024年安徽省教育厅科学研究项目(2024AH051732)2025安徽省教育厅科学研究项目(2025AHGXZK60243)2025年安徽省国家级大学生创新创业计划训练项目(202510381001S)淮南师范学院教学创新团队项目(2024hsjxtd02)
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