{"id":29453,"date":"2024-10-27T16:18:31","date_gmt":"2024-10-27T16:18:31","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29453"},"modified":"2024-11-26T06:52:34","modified_gmt":"2024-11-26T06:52:34","slug":"%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d-%eb%b0%8f-%eb%94%a5%eb%9f%ac%eb%8b%9d-%ec%95%8c%ea%b3%a0%eb%a6%ac%ec%a6%98-%ed%8a%b8%eb%a0%88%ec%9d%b4%eb%94%a9-%ed%8f%89%ea%b0%80-%ea%b2%b0%ea%b3%bc","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29453\/","title":{"rendered":"\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \ud3c9\uac00 \uacb0\uacfc"},"content":{"rendered":"<p><body><\/p>\n<p>\ubcf8 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ub300\ud574 \uc2ec\ub3c4 \uae4a\uc740 \ub17c\uc758\ub97c \uc9c4\ud589\ud558\uace0\uc790 \ud569\ub2c8\ub2e4. \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c \uc124\uacc4\uc5d0\uc11c\ubd80\ud130 \ubaa8\ub378 \ud559\uc2b5, \uc131\ub2a5 \ud3c9\uac00 \ubc0f \uc2e4\uc81c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uc801\uc6a9\uae4c\uc9c0 \uc54c\uae30 \uc27d\uac8c \uc124\uba85\ub4dc\ub9ac\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>1. \uc11c\ub860<\/h2>\n<p>\uae08\uc735\uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uc2dc\uac04\uc744 \uc808\uc57d\ud558\uace0 \ud310\ub2e8\uc758 \uc624\ub958\ub97c \uc904\uc5ec\uc904 \uc218 \uc788\ub294 \ud601\uc2e0\uc801\uc778 \uc811\uadfc \ubc29\uc2dd\uc785\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ubc95\uc740 \uacfc\uac70\uc758 \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\uc5ec \uc8fc\uac00 \uc608\uce21 \ubc0f \ud2b8\ub808\uc774\ub529 \uacb0\uc815\uc744 \uc9c0\uc6d0\ud558\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \uc54c\uace0\ub9ac\uc998\ub4e4\uc774 \uc5b4\ub5bb\uac8c \uc791\ub3d9\ud558\ub294\uc9c0, \uc5b4\ub5bb\uac8c \ud3c9\uac00\ub418\uace0 \uc788\ub294\uc9c0\ub97c \uad6c\uccb4\uc801\uc73c\ub85c \ubcf4\uc5ec\ub4dc\ub9b4 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<h2>2. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ucd08<\/h2>\n<h3>2.1 \uba38\uc2e0\ub7ec\ub2dd\uc758 \uac1c\ub150<\/h3>\n<p>\uba38\uc2e0\ub7ec\ub2dd\uc740 \ucef4\ud4e8\ud130\uac00 \uba85\uc2dc\uc801\uc778 \ud504\ub85c\uadf8\ub7a8 \uc5c6\uc774 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \ud559\uc2b5\ud558\ub294 \uae30\uc220\uc785\ub2c8\ub2e4. \uc774\ub294 \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\uacc4\ud559, \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \ud328\ud134 \uc778\uc2dd\uc758 \uacb0\ud569\uccb4\uc785\ub2c8\ub2e4. \uc54c\uace0\ub9ac\uc998\uc740 \uacfc\uac70 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \ud559\uc2b5\ud558\uc5ec \ubbf8\ub798\uc758 \uacb0\uacfc\ub97c \uc608\uce21\ud558\ub294 \ubaa8\ub378\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/p>\n<h3>2.2 \ub525\ub7ec\ub2dd\uc758 \ubc1c\uc804<\/h3>\n<p>\ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud558\uc704 \ubd84\uc57c\ub85c, \uc778\uacf5\uc2e0\uacbd\ub9dd\uc744 \ud65c\uc6a9\ud574 \ub370\uc774\ud130\uc758 \ub354 \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud569\ub2c8\ub2e4. \ud2b9\ud788, \uace0\ucc28\uc6d0 \ub370\uc774\ud130(\uc608: \ube44\ub514\uc624, \uc774\ubbf8\uc9c0, \uc790\uc5f0\uc5b4 \ucc98\ub9ac)\uc5d0 \ud6a8\uacfc\uc801\uc785\ub2c8\ub2e4. \uae08\uc735 \ub370\uc774\ud130 \ubd84\uc11d\uc5d0\uc11c\ub3c4 \uc2dc\uac04\uc774 \ud750\ub984\uc5d0 \ub530\ub77c \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud558\uace0 \uc608\uce21\ud558\ub294 \ub370 \uc720\uc6a9\ud558\uac8c \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>3. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc2dc\uc2a4\ud15c \uc124\uacc4<\/h2>\n<h3>3.1 \ub370\uc774\ud130 \uc218\uc9d1<\/h3>\n<p>\ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \uccab \ub2e8\uacc4\ub294 \uc801\uc808\ud55c \ub370\uc774\ud130 \uc218\uc9d1\uc785\ub2c8\ub2e4. \uc8fc\uac00, \uac70\ub798\ub7c9, \uac70\ub798 \ub300\uae08, \uacbd\uc81c \uc9c0\ud45c \ub4f1\uc758 \ub2e4\uc591\ud55c \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ub370\uc774\ud130\ub294 \uc8fc\uc2dd\uc774\ub098 \ud1b5\ud654\uc758 \uacfc\uac70 \uc131\uacfc\ub97c \ubc18\uc601\ud558\ubbc0\ub85c, \ubaa8\ub378 \ud559\uc2b5\uc5d0 \ub9e4\uc6b0 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4.<\/p>\n<h3>3.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n<p>\uc218\uc9d1\ud55c \ub370\uc774\ud130\ub294 \uc9c1\uc811 \uc0ac\uc6a9\ud558\uae30 \uc804\uc5d0 \uc804\ucc98\ub9ac \uacfc\uc815\uc744 \uac70\uccd0\uc57c \ud569\ub2c8\ub2e4. \uacb0\uce21\uce58 \ucc98\ub9ac, \ub370\uc774\ud130 \uc2a4\ucf00\uc77c\ub9c1, \uc6d0-\ud56b \uc778\ucf54\ub529\uacfc \uac19\uc740 \uae30\ubc95\ub4e4\uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4. \ud2b9\ud788 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc5d0\uc11c\ub294 \ub370\uc774\ud130\uc758 \uc2a4\ucf00\uc77c\ub9c1\uc774 \uc131\ub2a5\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce69\ub2c8\ub2e4.<\/p>\n<h3>3.3 \ud53c\uccd0 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1<\/h3>\n<p>\ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ub192\uc774\uae30 \uc704\ud574\uc11c\ub294 \uc801\uc808\ud55c \ud53c\uccd0(\ud2b9\uc9d5) \uc120\ud0dd\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \uc774\ub3d9 \ud3c9\uade0, \uc0c1\ub300 \uac15\ub3c4 \uc9c0\uc218(RSI), MACD \ub4f1\uc758 \uae30\uc220\uc801 \uc9c0\ud45c\ub97c \ud1b5\ud574 \uc0c8\ub85c\uc6b4 \ud53c\uccd0\ub97c \uc0dd\uc131\ud558\uace0, \uc774\ub97c \ud1b5\ud574 \uc2dc\uc7a5\uc5d0\uc11c\uc758 \ub3d9\ud5a5\uc744 \ub354 \uc798 \ud30c\uc545\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4.<\/p>\n<h2>4. \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378 \uad6c\ucd95<\/h2>\n<h3>4.1 \ubaa8\ub378 \uc120\ud0dd<\/h3>\n<p>\uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub2e4\uc591\ud55c \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. \ud68c\uadc0 \ubd84\uc11d, \uacb0\uc815 \ud2b8\ub9ac, \ub79c\ub364 \ud3ec\ub808\uc2a4\ud2b8, SVM, \uc2e0\uacbd\ub9dd \ub4f1\uc774 \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uac01\uac01\uc758 \uc54c\uace0\ub9ac\uc998\ub9c8\ub2e4 \ud2b9\uc9d5\uc774 \uc788\uc73c\ubbc0\ub85c, \ud2b9\uc815 \ubb38\uc81c\uc5d0 \ub9de\ub294 \ucd5c\uc801\uc758 \uc54c\uace0\ub9ac\uc998\uc744 \uc120\ud0dd\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n<h3>4.2 \ubaa8\ub378 \ud559\uc2b5<\/h3>\n<p>\ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0a4\uae30 \uc704\ud574\uc11c\ub294 \uacfc\uac70 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc54c\uace0\ub9ac\uc998\uc774 \uc608\uce21\ud560 \uc218 \uc788\ub3c4\ub85d \uc9c0\ub3c4 \ud559\uc2b5 \ubc29\uc2dd\uc73c\ub85c \ud559\uc2b5\uc744 \uc9c4\ud589\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 \ud559\uc2b5 \ub370\uc774\ud130\uc640 \uac80\uc99d \ub370\uc774\ud130\ub97c \ubd84\ub9ac\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>from sklearn.model_selection import train_test_split\n# \ub370\uc774\ud130\ub97c X\uc640 y\ub85c \ub098\ub204\uace0, \ud6c8\ub828-\uac80\uc99d \ub370\uc774\ud130 \ubd84\ub9ac\nX_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=42)<\/code><\/pre>\n<h2>5. \ub525\ub7ec\ub2dd \ubaa8\ub378 \uad6c\ucd95<\/h2>\n<h3>5.1 \uc2e0\uacbd\ub9dd \uad6c\uc870 \uc124\uacc4<\/h3>\n<p>\ub525\ub7ec\ub2dd\uc5d0\uc11c\ub294 \uc778\uacf5\uc2e0\uacbd\ub9dd\uc758 \uce35\uc744 \uae4a\uac8c \uc313\uc544 \ub354\uc6b1 \ubcf5\uc7a1\ud55c \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 Keras\uc640 \uac19\uc740 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc2e0\uacbd\ub9dd \ubaa8\ub378\uc744 \uad6c\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>from keras.models import Sequential\nfrom keras.layers import Dense\n\n# \ubaa8\ub378 \uc815\uc758\nmodel = Sequential()\nmodel.add(Dense(64, input_dim=X_train.shape[1], activation='relu'))\nmodel.add(Dense(32, activation='relu'))\nmodel.add(Dense(1, activation='linear'))<\/code><\/pre>\n<h3>5.2 \ubaa8\ub378 \ucef4\ud30c\uc77c \ubc0f \ud6c8\ub828<\/h3>\n<p>\ubaa8\ub378\uc744 \ucef4\ud30c\uc77c\ud560 \ub54c \uc0ac\uc6a9\ud560 \uc190\uc2e4 \ud568\uc218\uc640 \ucd5c\uc801\ud654 \uc54c\uace0\ub9ac\uc998\uc744 \uc124\uc815\ud569\ub2c8\ub2e4. \uc774\ud6c4 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0a4\uace0, \ud559\uc2b5\ud55c \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>model.compile(loss='mean_squared_error', optimizer='adam')\nmodel.fit(X_train, y_train, epochs=100, batch_size=32, validation_data=(X_val, y_val))<\/code><\/pre>\n<h2>6. \uc131\ub2a5 \ud3c9\uac00<\/h2>\n<h3>6.1 \ud3c9\uac00 \uc9c0\ud45c<\/h3>\n<p>\ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud55c \uc5ec\ub7ec \uc9c0\ud45c\ub4e4\uc774 \uc788\uc2b5\ub2c8\ub2e4. RMSE, MAE, R\u00b2 \uc810\uc218 \ub4f1 \ub2e4\uc591\ud55c \uc9c0\ud45c\ub97c \ud65c\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc608\uce21 \uc815\ud655\ub3c4\ub97c \ubd84\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>from sklearn.metrics import mean_squared_error\n\n# \uc608\uce21 \uacb0\uacfc\ny_pred = model.predict(X_val)\n\n# RMSE \uacc4\uc0b0\nrmse = mean_squared_error(y_val, y_pred, squared=False)\nprint(f'RMSE: {rmse:.4f}')<\/code><\/pre>\n<h3>6.2 \uad50\ucc28 \uac80\uc99d<\/h3>\n<p>\ubaa8\ub378\uc758 \uc77c\ubc18\ud654 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 \uad50\ucc28 \uac80\uc99d\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ubaa8\ub378\uc774 \ub2e4\uc591\ud55c \ub370\uc774\ud130\uc5d0\uc11c \uc5bc\ub9c8\ub098 \uc798 \uc77c\ubc18\ud654\ub418\ub294\uc9c0\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>7. \uc2e4\uc81c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uc801\uc6a9<\/h2>\n<h3>7.1 \ub9e4\ub9e4 \uc2e0\ud638 \uc0dd\uc131<\/h3>\n<p>\uc608\uce21\ud55c \uc8fc\uac00\ub97c \ubc14\ud0d5\uc73c\ub85c \ub9e4\uc218 \ub610\ub294 \ub9e4\ub3c4 \uc2e0\ud638\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4. \uc774 \uc2e0\ud638\ub294 \ud2b9\uc815 \uae30\uc900\uc744 \ub9cc\uc871\ud560 \ub54c \ub9e4\ub9e4\ub97c \uc2e4\ud589\ud558\ub3c4\ub85d \uc124\uc815\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>signal = []\nfor i in range(len(predictions)):\n    if predictions[i] &gt; current_price:  # \ub9e4\uc218 \uc2e0\ud638\n        signal.append(1)\n    else:  # \ub9e4\ub3c4 \uc2e0\ud638\n        signal.append(-1)<\/code><\/pre>\n<h3>7.2 \ubc31\ud14c\uc2a4\ud2b8 \uc218\ud589<\/h3>\n<p>\uc2e4\uc81c \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc804\ub7b5 \ud6a8\uacfc\ub97c \uac80\uc99d\ud558\uae30 \uc704\ud574 \ubc31\ud14c\uc2a4\ud305\uc744 \uc9c4\ud589\ud569\ub2c8\ub2e4. \uacfc\uac70 \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud558\uc5ec \ud574\ub2f9 \uc804\ub7b5\ub300\ub85c \ub9e4\ub9e4\ub97c \uc9c4\ud589\ud588\uc744 \ub54c\uc758 \uc131\uacfc\ub97c \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/p>\n<h2>8. \ud3c9\uac00 \uacb0\uacfc \ubd84\uc11d<\/h2>\n<h3>8.1 \uc218\uc775\ub960 \ubd84\uc11d<\/h3>\n<p>\ubc31\ud14c\uc2a4\ud2b8 \uacb0\uacfc\ub97c \ubc14\ud0d5\uc73c\ub85c \ucd5c\uc885 \uc218\uc775\ub960\uc744 \uc0b0\ucd9c\ud558\uace0 \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \uc131\uacfc\ub97c \ubd84\uc11d\ud569\ub2c8\ub2e4. \ub2e8\uc21c\ud788 \uc218\uc775\ub960\ub9cc\uc774 \uc544\ub2c8\ub77c, \ub9ac\uc2a4\ud06c \uc870\uc815 \uc218\uc775\ub960\ub3c4 \uace0\ub824\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n<pre><code>final_profit = calculate_final_profit(signals, prices)\nprint(f'\ucd5c\uc885 \uc218\uc775\ub960: {final_profit:.2f}%')<\/code><\/pre>\n<h3>8.2 \ub2e4\uc591\ud55c \uc2dc\ub098\ub9ac\uc624 \ubd84\uc11d<\/h3>\n<p>\uc804\ub7b5\uc758 \uc131\uacfc\ub97c \uac80\uc99d\ud558\uae30 \uc704\ud574 \ub2e4\uc591\ud55c \uc2dc\ub098\ub9ac\uc624\uc640 \uc2dc\uc7a5 \uc870\uac74\uc5d0\uc11c\uc758 \uc131\uacfc\ub97c \ubd84\uc11d\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ubaa8\ub378\uc758 \uacac\uace0\ud568\uacfc \ub2e4\uc591\uc131\uc5d0 \ub300\ud55c \uc774\ud574\ub97c \ub192\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>9. \uacb0\ub860<\/h2>\n<p>\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc740 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uc0c8\ub85c\uc6b4 \ud328\ub7ec\ub2e4\uc784\uc744 \uc5f4\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \uae30\ubc95\ub4e4\uc744 \ud1b5\ud574 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uace0 \ud3c9\uac00\ud558\ub294 \uacfc\uc815\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ub05d\uc73c\ub85c, \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uc9c0\uc18d\uc801\uc73c\ub85c \uac1c\uc120\ud558\uace0 \uc2e4\uc81c \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc801\uc6a9 \uac00\ub2a5\uc131\uc744 \ub192\uc774\uae30 \uc704\ud574\uc11c\ub294 \ub04a\uc784\uc5c6\ub294 \uc5f0\uad6c\uc640 \uc2e4\ud5d8\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n<h2>10. \ucc38\uace0\ubb38\ud5cc<\/h2>\n<ul>\n<li>1. &#8220;Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow&#8221; by Aur\u00e9lien G\u00e9ron<\/li>\n<li>2. &#8220;Deep Learning for Finance&#8221; by Jannes Klaas<\/li>\n<li>3. &#8220;Advances in Financial Machine Learning&#8221; by Marcos L\u00f3pez de Prado<\/li>\n<\/ul>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ubcf8 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ub300\ud574 \uc2ec\ub3c4 \uae4a\uc740 \ub17c\uc758\ub97c \uc9c4\ud589\ud558\uace0\uc790 \ud569\ub2c8\ub2e4. \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c \uc124\uacc4\uc5d0\uc11c\ubd80\ud130 \ubaa8\ub378 \ud559\uc2b5, \uc131\ub2a5 \ud3c9\uac00 \ubc0f \uc2e4\uc81c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uc801\uc6a9\uae4c\uc9c0 \uc54c\uae30 \uc27d\uac8c \uc124\uba85\ub4dc\ub9ac\uaca0\uc2b5\ub2c8\ub2e4. 1. \uc11c\ub860 \uae08\uc735\uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uc2dc\uac04\uc744 \uc808\uc57d\ud558\uace0 \ud310\ub2e8\uc758 \uc624\ub958\ub97c \uc904\uc5ec\uc904 \uc218 \uc788\ub294 \ud601\uc2e0\uc801\uc778 \uc811\uadfc \ubc29\uc2dd\uc785\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ubc95\uc740 \uacfc\uac70\uc758 \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\uc5ec \uc8fc\uac00 \uc608\uce21 \ubc0f \ud2b8\ub808\uc774\ub529 &hellip; <a href=\"https:\/\/atmokpo.com\/w\/29453\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \ud3c9\uac00 \uacb0\uacfc&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[29],"tags":[],"class_list":["post-29453","post","type-post","status-publish","format-standard","hentry","category-29"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \ud3c9\uac00 \uacb0\uacfc - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/29453\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" 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