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首页> 外文期刊>International journal of applied evolutionary computation >Optimal Kernel and Wavelet Coefficients to Support Vector Regression Model and Wavelet Neural Network for Time Series Rainfall Prediction
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Optimal Kernel and Wavelet Coefficients to Support Vector Regression Model and Wavelet Neural Network for Time Series Rainfall Prediction

机译：支持向量回归模型和小波神经网络的时间序列降雨预测的最优核和小波系数

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摘要

Rainfall prediction is an active topic recently since people want to make decisions about crop and irrigation cycles to understand weather and climate patterns. Due to need of predicting this natural phenomenon, various research works has been carried out previously with different type of techniques using historical data. In this paper, a hybrid model based on support vector regression (SVR) model and wavelet neural network (WNN) for rainfall prediction is proposed. In hybridized SVR-WNN, optimal kernel andwavelet coefficients are generated using hybrid algorithm. Here, artificial bee colony (ABC) and genetic algorithm (GA) are hybridized and used to this purpose. These optimal kernel functions and wavelet coefficients are supplied to hybrid model to predict the rainfall. In hybrid model, wavelet neural network with ARX modeling and support vector regression (SVR) model is effectively hybridized to time series rainfall prediction. The performance of the hybrid model is analyzed with the help of real datasets taken from Assam, Chhattisgarh, East Rajasthan, Gangetic West Bengal, Gujarath, Haryana, Telangana, Rajalaseema regions. From the results, it can be concluded that proposed rainfall prediction model have shown the MAPE performance of 20, the RMSE performance of 2, MAD performance of 12, but existing model show the MAPE performance of 61, the RMSE performance of 3, MAD performance of 27 for Telangana dataset.
机译：由于人们希望对作物和灌溉周期做出决策，以了解天气和气候模式，因此降雨预测是最近的一个活跃话题。由于需要预测这种自然现象，因此以前使用历史数据以不同类型的技术进行了各种研究工作。提出了一种基于支持向量回归（SVR）模型和小波神经网络（WNN）的降雨预测混合模型。在混合SVR-WNN中，使用混合算法生成最优内核和小波系数。在这里，人工蜂群（ABC）和遗传算法（GA）被杂交并用于此目的。这些最优的核函数和小波系数被提供给混合模型以预测降雨。在混合模型中，将具有ARX建模和支持向量回归（SVR）模型的小波神经网络有效地与时间序列降雨预测进行了混合。借助从阿萨姆邦，恰蒂斯加尔邦，东拉贾斯坦邦，恒河西孟加拉邦，古吉拉特邦，哈里亚纳邦，特兰甘纳邦，拉贾拉塞玛地区收集的真实数据集，分析了混合模型的性能。从结果可以得出结论，提出的降雨预测模型显示出MAPE性能为20，RMSE性能为2，MAD性能为12，但是现有模型显示MAPE性能为61，RMSE性能为3，MAD性能对于Telangana数据集为27。

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