import random

#--------粒　子　群　最　適　化------------------------------

#評価関数: 
def criterion(x, y):
    z=-abs(k-(x*(x+1))/2)
    if x<0:
      z=-10000000000

    return z

#粒子の位置の更新を行う関数
def update_position(x, y, vx, vy):
    new_x = x + vx
    new_y = y + vy
    return new_x, new_y

#粒子の速度の更新を行う関数
def update_velocity(x, y, vx, vy, p, g, w=1, ro_max=1,v_max=100):
    #パラメーターroはランダムに与える
    ro1 = random.uniform(0, ro_max)
    ro2 = random.uniform(0, ro_max)
    #粒子速度の更新を行う
    new_vx = int(w * vx + ro1 * (p[0] - x) + ro2 * (g[0] - x))
    if abs(new_vx)>v_max:
        new_vx=int(v_max*new_vx/abs(new_vx))

    new_vy = w * vy + ro1 * (p[1] - y) + ro2 * (g[1] - y)
    return new_vx, new_vy

def main():
    N = 1000  #粒子の数
    x_min, x_max = 0, k
    y_min, y_max = 0, 0
    #粒子位置, 速度, パーソナルベスト, グローバルベストの初期化を行う
    ps = [[random.randint(x_min, x_max), random.uniform(y_min, y_max)] for i in range(N)]
    vs = [[0.0, 0.0] for i in range(N)]

    personal_best_positions = list(ps)
    personal_best_scores = [criterion(p[0], p[1]) for p in ps]
    best_particle = personal_best_scores.index(max(personal_best_scores))
    global_best_position = personal_best_positions[best_particle]


    T = 600  #世代数(ループの回数)
    for t in range(T):
        for n in range(N):
            x, y = ps[n][0], ps[n][1]
            vx, vy = vs[n][0], vs[n][1]
            p = personal_best_positions[n]

            #粒子の位置の更新を行う
            new_x, new_y = update_position(x, y, vx, vy)
            ps[n] = [new_x, new_y]

            #粒子の速度の更新を行う
            new_vx, new_vy = update_velocity(new_x, new_y, vx, vy, p, global_best_position)
            vs[n] = [new_vx, new_vy]

            #評価値を求め, パーソナルベストの更新を行う
            score = criterion(new_x, new_y)
            if score > personal_best_scores[n]:
                personal_best_scores[n] = score
                personal_best_positions[n] = [new_x, new_y]

        #グローバルベストの更新を行う
        best_particle = personal_best_scores.index(max(personal_best_scores))
        global_best_position = personal_best_positions[best_particle]

        if k==(global_best_position[0]*(global_best_position[0]+1))//2:
          print("YES")
          print(int(global_best_position[0]))
          exit()
 


    #最適解

#    print(max(personal_best_scores), global_best_position)
    return max(personal_best_scores), global_best_position[0], global_best_position[1]
#--------------------------------------------------------------

k=int(input())
best=-100000000000000
xx=0
yy=0
for i in range(3):
    kouho_best, kouho_x, kouho_y=main()
    if best>kouho_best:
        best=kouho_best
        xx=kouho_x
        yy=kouho_y
 
print("NO")