function [train_data, val_data] = train_val_split(...
    train_data, train_num)
    for i = 1:size(train_data, 2)
        % 随机选择一个起点，需要保证这train_num个训练集是连续的
        train_start = randi(size(train_data(i).features, 1)-train_num+1);
        train_range = train_start:(train_start + train_num-1);
        val_range = setdiff(1:size(train_data(i).features, 1), train_range);
        x_train = train_data(i).features(train_range, :);
        y_train = train_data(i).resTime(train_range);
        x_val = train_data(i).features(val_range, :);
        y_val = train_data(i).resTime(val_range);
        train_data(i).features = x_train;
        train_data(i).resTime = y_train;
        val_data(i).features = x_val;
        val_data(i).resTime = y_val;
    end
end