Wind farms have a focus role in environmentally friendly energy production. There are short-term estimates of wind speed in planning energy production in wind power plants. In this article, we analyzed the wind speed in the Istanbul Avcılar region by an artificial neural network method (ANN) and regression method. One of the methods commonly used in estimation processes is Nonlinear Autoregressive Exogenous (NARX). We divide the data into three parts 70%, 15%, and 15%, respectively, for learning, validation, and testing. We used the Levenberg–Marquardt (LM) algorithm for data network training. We compared the predicted wind speed with the measured and tested values. We used MATLAB software in the analysis of the model. We obtained system outputs and regression models of wind speed with artificial neural network simulations. Besides, we calculated the effect sizes.

风电场在环保能源生产方面发挥着重要作用。在规划风力发电厂的能源生产时有对风速的短期估计。在本文中，我们通过人工神经网络方法 (ANN) 和回归方法分析了伊斯坦布尔 Avcılar 地区的风速。估计过程中常用的方法之一是非线性自回归外生 (NARX)。我们将数据分为 70%、15% 和 15% 三个部分，分别用于学习、验证和测试。我们使用 Levenberg-Marquardt (LM) 算法进行数据网络训练。我们将预测的风速与测量值和测试值进行了比较。我们在模型分析中使用了MATLAB软件。我们通过人工神经网络模拟获得了风速的系统输出和回归模型。除了，