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  • 2-21 小综合:人工神经网络逼近股票价格3

    import tensorflow as tf
    import numpy as np
    import matplotlib.pyplot as plt
    date = np.linspace(1,15,15)
    endPrice = np.array([2511.90,2538.26,2510.68,2591.66,2732.98,2701.69,2701.29,2678.67,2726.50,2681.50,2739.17,2715.07,2823.58,2864.90,2919.08])
    beginPrice = np.array([2438.71,2500.88,2534.95,2512.52,2594.04,2743.26,2697.47,2695.24,2678.23,2722.13,2674.93,2744.13,2717.46,2832.73,2877.40])
    print(date)
    plt.figure()
    for i in range(0,15):
        # 1 柱状图
        dateOne = np.zeros([2])
        dateOne[0] = i;
        dateOne[1] = i;
        priceOne = np.zeros([2])
        priceOne[0] = beginPrice[i]
        priceOne[1] = endPrice[i]
        if endPrice[i]>beginPrice[i]:
            plt.plot(dateOne,priceOne,'r',lw=8)
        else:
            plt.plot(dateOne,priceOne,'g',lw=8)
    plt.show()
    # A(15*1)*w1(1*10)+b1(1*10) = B(15*10)
    # B(15*10)*w2(10*1)+b2(15*1) = C(15*1)
    # 1 A B C
    dateNormal = np.zeros([15,1])
    priceNormal = np.zeros([15,1])
    for i in range(0,15):
        dateNormal = i/14.0;
        priceNormal = endPrice[i]/3000.0;
    x = tf.placeholder(tf.float32,[None,1])# N行1列的
    y = tf.placeholder(tf.float32,[None,1])
    # B
    w1 = tf.Variable(tf.random_uniform([1,10],0,1))
    b1 = tf.Variable(tf.zeros([1,10]))
    wb1 = tf.matmul(x,w1)+b1
    layer1 = tf.nn.relu(wb1) # 激励函数
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  • 原文地址:https://www.cnblogs.com/ZHONGZHENHUA/p/9665698.html
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