Supporting data set for : Artificial Neural Network-based Repair and Maintenance Cost Estimation Model for Rice Combine Harvester

This data consist of : 1. Accumulative R&M cost vs. harvest area (North region). 2. Accumulative R&M cost vs. harvest area (Northeast region). 3. Accumulative R&M cost vs. harvest area (Central region). 4. Conventional R&M cost equation based on power function-fitted coefficients. 5. ANN target R&M cost data. 6. ANN training data. 7.ANN trained network. (MATLAB model) 8.ANN-based R&M cost estimation model. (MATLAB model) 9.Curve fitting coefficients (power function-fitted) of North region. 10.Curve fitting coefficients (power function-fitted) of Northeast region. 11.Curve fitting coefficients (power function-fitted) of Central region.本数据集包含以下内容： 1. 累计维修维护（Repair & Maintenance, R&M）成本与收获面积的对应关系（北部地区） 2. 累计维修维护成本与收获面积的对应关系（东北地区） 3. 累计维修维护成本与收获面积的对应关系（中部地区） 4. 基于幂函数拟合系数的常规维修维护成本方程 5. 人工神经网络（Artificial Neural Network, ANN）目标维修维护成本数据 6. 人工神经网络训练数据 7. 已训练的人工神经网络（MATLAB模型） 8. 基于人工神经网络的维修维护成本估算模型（MATLAB模型） 9. 北部地区幂函数拟合曲线系数 10. 东北地区幂函数拟合曲线系数 11. 中部地区幂函数拟合曲线系数