{"id":479331,"date":"2023-08-09T10:33:53","date_gmt":"2023-08-09T10:33:53","guid":{"rendered":""},"modified":"2023-09-05T11:18:37","modified_gmt":"2023-09-05T11:18:37","slug":"time-series-decomposition","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/time-series-decomposition\/","title":{"rendered":"Ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian"},"content":{"rendered":"<p>Ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian \u0111\u1ec1 c\u1eadp \u0111\u1ebfn qu\u00e1 tr\u00ecnh chia nh\u1ecf t\u1eadp d\u1eef li\u1ec7u chu\u1ed7i th\u1eddi gian th\u00e0nh c\u00e1c ph\u1ea7n c\u1ea5u th\u00e0nh \u0111\u1ec3 hi\u1ec3u c\u00e1c m\u00f4 h\u00ecnh v\u00e0 h\u00e0nh vi c\u01a1 b\u1ea3n. C\u00e1c th\u00e0nh ph\u1ea7n n\u00e0y th\u01b0\u1eddng bao g\u1ed3m c\u00e1c th\u00e0nh ph\u1ea7n xu h\u01b0\u1edbng, theo m\u00f9a, theo chu k\u1ef3 v\u00e0 kh\u00f4ng th\u01b0\u1eddng xuy\u00ean ho\u1eb7c ng\u1eabu nhi\u00ean. Vi\u1ec7c ph\u00e2n t\u00edch c\u00e1c th\u00e0nh ph\u1ea7n n\u00e0y m\u1ed9t c\u00e1ch ri\u00eang bi\u1ec7t c\u00f3 th\u1ec3 cung c\u1ea5p c\u00e1i nh\u00ecn s\u00e2u s\u1eafc v\u1ec1 c\u1ea5u tr\u00fac c\u01a1 b\u1ea3n c\u1ee7a d\u1eef li\u1ec7u v\u00e0 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n cho vi\u1ec7c d\u1ef1 b\u00e1o v\u00e0 ph\u00e2n t\u00edch t\u1ed1t h\u01a1n.<\/p>\n<h2>L\u1ecbch s\u1eed ngu\u1ed3n g\u1ed1c c\u1ee7a s\u1ef1 ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>S\u1ef1 ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian c\u00f3 ngu\u1ed3n g\u1ed1c t\u1eeb \u0111\u1ea7u th\u1ebf k\u1ef7 20, \u0111\u1eb7c bi\u1ec7t l\u00e0 v\u1edbi c\u00f4ng tr\u00ecnh c\u1ee7a c\u00e1c nh\u00e0 kinh t\u1ebf nh\u01b0 WS Jevons v\u00e0 Simon Kuznets. \u00dd t\u01b0\u1edfng n\u00e0y \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n s\u00e2u h\u01a1n v\u00e0o nh\u1eefng n\u0103m 1920 v\u00e0 1930 b\u1edfi c\u00e1c nh\u00e0 kinh t\u1ebf h\u1ecdc nh\u01b0 Wesley C. Mitchell. M\u1ee5c ti\u00eau l\u00e0 t\u00e1ch bi\u1ec7t c\u00e1c chuy\u1ec3n \u0111\u1ed9ng mang t\u00ednh chu k\u1ef3 trong d\u1eef li\u1ec7u kinh t\u1ebf kh\u1ecfi c\u00e1c xu h\u01b0\u1edbng v\u00e0 c\u00e1c bi\u1ebfn \u0111\u1ed9ng kh\u00e1c.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian. M\u1edf r\u1ed9ng ph\u00e2n t\u00edch chu\u1ed7i th\u1eddi gian ch\u1ee7 \u0111\u1ec1<\/h2>\n<p>Ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian li\u00ean quan \u0111\u1ebfn vi\u1ec7c chia d\u1eef li\u1ec7u chu\u1ed7i th\u1eddi gian th\u00e0nh nhi\u1ec1u th\u00e0nh ph\u1ea7n c\u01a1 b\u1ea3n, c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c ph\u00e2n t\u00edch ri\u00eang bi\u1ec7t. \u0110\u00e2y th\u01b0\u1eddng l\u00e0:<\/p>\n<ul>\n<li><strong>Xu h\u01b0\u1edbng<\/strong>: S\u1ef1 chuy\u1ec3n \u0111\u1ed9ng d\u00e0i h\u1ea1n c\u1ee7a d\u1eef li\u1ec7u.<\/li>\n<li><strong>theo m\u00f9a<\/strong>: C\u00e1c m\u1eabu l\u1eb7p l\u1ea1i trong m\u1ed9t kho\u1ea3ng th\u1eddi gian c\u1ed1 \u0111\u1ecbnh, ch\u1eb3ng h\u1ea1n nh\u01b0 m\u1ed9t n\u0103m ho\u1eb7c m\u1ed9t tu\u1ea7n.<\/li>\n<li><strong>theo chu k\u1ef3<\/strong>: Nh\u1eefng bi\u1ebfn \u0111\u1ed9ng x\u1ea3y ra kh\u00f4ng \u0111\u1ec1u \u0111\u1eb7n, th\u01b0\u1eddng li\u00ean quan \u0111\u1ebfn chu k\u1ef3 kinh t\u1ebf.<\/li>\n<li><strong>kh\u00f4ng th\u01b0\u1eddng xuy\u00ean<\/strong>: C\u00e1c chuy\u1ec3n \u0111\u1ed9ng ng\u1eabu nhi\u00ean ho\u1eb7c kh\u00f4ng th\u1ec3 \u0111o\u00e1n tr\u01b0\u1edbc trong d\u1eef li\u1ec7u.<\/li>\n<\/ul>\n<p>Vi\u1ec7c ph\u00e2n t\u00e1ch c\u00f3 th\u1ec3 \u0111\u1ea1t \u0111\u01b0\u1ee3c th\u00f4ng qua nhi\u1ec1u ph\u01b0\u01a1ng ph\u00e1p kh\u00e1c nhau nh\u01b0 \u0111\u01b0\u1eddng trung b\u00ecnh \u0111\u1ed9ng, l\u00e0m m\u1ecbn h\u00e0m m\u0169 v\u00e0 m\u00f4 h\u00ecnh th\u1ed1ng k\u00ea nh\u01b0 ARIMA.<\/p>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a s\u1ef1 ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian. C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng c\u1ee7a qu\u00e1 tr\u00ecnh ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian<\/h2>\n<p>Ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch t\u00e1ch c\u00e1c th\u00e0nh ph\u1ea7n kh\u00e1c nhau c\u1ee7a chu\u1ed7i:<\/p>\n<ol>\n<li><strong>Th\u00e0nh ph\u1ea7n xu h\u01b0\u1edbng<\/strong>: Th\u01b0\u1eddng \u0111\u01b0\u1ee3c tr\u00edch xu\u1ea5t b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng \u0111\u01b0\u1eddng trung b\u00ecnh \u0111\u1ed9ng ho\u1eb7c l\u00e0m m\u1ecbn h\u00e0m m\u0169.<\/li>\n<li><strong>Th\u00e0nh ph\u1ea7n theo m\u00f9a<\/strong>: \u0110\u01b0\u1ee3c ph\u00e1t hi\u1ec7n b\u1eb1ng c\u00e1ch x\u00e1c \u0111\u1ecbnh c\u00e1c m\u1eabu l\u1eb7p l\u1ea1i trong kho\u1ea3ng th\u1eddi gian c\u1ed1 \u0111\u1ecbnh.<\/li>\n<li><strong>Th\u00e0nh ph\u1ea7n mang t\u00ednh chu k\u1ef3<\/strong>: \u0110\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh b\u1eb1ng c\u00e1ch ph\u00e2n t\u00edch c\u00e1c bi\u1ebfn \u0111\u1ed9ng x\u1ea3y ra \u1edf nh\u1eefng kho\u1ea3ng th\u1eddi gian kh\u00f4ng \u0111\u1ec1u.<\/li>\n<li><strong>Th\u00e0nh ph\u1ea7n kh\u00f4ng \u0111\u1ec1u<\/strong>: Nh\u1eefng g\u00ec c\u00f2n l\u1ea1i sau khi tr\u00edch xu\u1ea5t c\u00e1c th\u00e0nh ph\u1ea7n kh\u00e1c, th\u01b0\u1eddng \u0111\u01b0\u1ee3c coi l\u00e0 nhi\u1ec5u ho\u1eb7c l\u1ed7i.<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh c\u1ee7a ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian<\/h2>\n<ul>\n<li><strong>S\u1ef1 ch\u00ednh x\u00e1c<\/strong>: Cho ph\u00e9p d\u1ef1 b\u00e1o v\u00e0 hi\u1ec3u bi\u1ebft ch\u00ednh x\u00e1c h\u01a1n.<\/li>\n<li><strong>T\u00ednh linh ho\u1ea1t<\/strong>: C\u00f3 th\u1ec3 \u00e1p d\u1ee5ng cho nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau nh\u01b0 kinh t\u1ebf, t\u00e0i ch\u00ednh, khoa h\u1ecdc m\u00f4i tr\u01b0\u1eddng.<\/li>\n<li><strong>\u0110\u1ed9 ph\u1ee9c t\u1ea1p<\/strong>: C\u00f3 th\u1ec3 y\u00eau c\u1ea7u c\u00e1c ph\u01b0\u01a1ng ph\u00e1p th\u1ed1ng k\u00ea ph\u1ee9c t\u1ea1p v\u00e0 ki\u1ebfn th\u1ee9c chuy\u00ean m\u00f4n.<\/li>\n<\/ul>\n<h2>C\u00e1c ki\u1ec3u ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian<\/h2>\n<p>Ch\u1ee7 y\u1ebfu c\u00f3 hai lo\u1ea1i:<\/p>\n<ol>\n<li><strong>M\u00f4 h\u00ecnh ph\u1ee5 gia<\/strong>\n<ul>\n<li>Xu h\u01b0\u1edbng + Theo m\u00f9a + Theo chu k\u1ef3 + Kh\u00f4ng th\u01b0\u1eddng xuy\u00ean<\/li>\n<\/ul>\n<\/li>\n<li><strong>M\u00f4 h\u00ecnh nh\u00e2n<\/strong>\n<ul>\n<li>Xu h\u01b0\u1edbng \u00d7 Theo m\u00f9a \u00d7 Chu k\u1ef3 \u00d7 Kh\u00f4ng th\u01b0\u1eddng xuy\u00ean<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>Ph\u00f9 h\u1ee3p v\u1edbi<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>ph\u1ee5 gia<\/td>\n<td>Xu h\u01b0\u1edbng tuy\u1ebfn t\u00ednh v\u00e0 bi\u1ebfn \u0111\u1ed5i theo m\u00f9a<\/td>\n<\/tr>\n<tr>\n<td>nh\u00e2n<\/td>\n<td>Xu h\u01b0\u1edbng c\u1ea5p s\u1ed1 nh\u00e2n v\u00e0 ph\u1ea7n tr\u0103m thay \u0111\u1ed5i<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng Ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng<\/h2>\n<h3>C\u00f4ng d\u1ee5ng<\/h3>\n<ul>\n<li>D\u1ef1 b\u00e1o xu h\u01b0\u1edbng t\u01b0\u01a1ng lai.<\/li>\n<li>X\u00e1c \u0111\u1ecbnh c\u00e1c m\u1eabu c\u01a1 b\u1ea3n<\/li>\n<li>Ph\u00e1t hi\u1ec7n s\u1ef1 b\u1ea5t th\u01b0\u1eddng.<\/li>\n<\/ul>\n<h3>V\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p<\/h3>\n<ul>\n<li><strong>Trang b\u1ecb qu\u00e1 m\u1ee9c<\/strong>: Tr\u00e1nh s\u1eed d\u1ee5ng c\u00e1c m\u00f4 h\u00ecnh qu\u00e1 ph\u1ee9c t\u1ea1p.<\/li>\n<li><strong>V\u1ea5n \u0111\u1ec1 v\u1ec1 ch\u1ea5t l\u01b0\u1ee3ng d\u1eef li\u1ec7u<\/strong>: \u0110\u1ea3m b\u1ea3o d\u1eef li\u1ec7u s\u1ea1ch s\u1ebd v\u00e0 \u0111\u01b0\u1ee3c chu\u1ea9n b\u1ecb t\u1ed1t.<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 nh\u1eefng so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u0111\u1eb7c tr\u01b0ng<\/th>\n<th>Ph\u00e2n t\u00edch chu\u1ed7i th\u1eddi gian<\/th>\n<th>Ph\u00e2n t\u00edch Fourier<\/th>\n<th>Ph\u00e2n t\u00edch b\u01b0\u1edbc s\u00f3ng<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>T\u1eadp trung<\/td>\n<td>Xu h\u01b0\u1edbng, Theo m\u00f9a<\/td>\n<td>T\u00ednh th\u01b0\u1eddng xuy\u00ean<\/td>\n<td>Th\u1eddi gian v\u00e0 t\u1ea7n su\u1ea5t<\/td>\n<\/tr>\n<tr>\n<td>\u0110\u1ed9 ph\u1ee9c t\u1ea1p<\/td>\n<td>V\u1eeba ph\u1ea3i<\/td>\n<td>T\u1ed5 h\u1ee3p<\/td>\n<td>R\u1ea5t ph\u1ee9c t\u1ea1p<\/td>\n<\/tr>\n<tr>\n<td>C\u00e1c \u1ee9ng d\u1ee5ng<\/td>\n<td>Kinh t\u1ebf, Kinh doanh<\/td>\n<td>X\u1eed l\u00fd t\u00edn hi\u1ec7u<\/td>\n<td>Ph\u00e2n t\u00edch h\u00ecnh \u1ea3nh<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn s\u1ef1 ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian<\/h2>\n<p>C\u00e1c tri\u1ec3n v\u1ecdng trong t\u01b0\u01a1ng lai bao g\u1ed3m vi\u1ec7c t\u00edch h\u1ee3p c\u00e1c k\u1ef9 thu\u1eadt h\u1ecdc m\u00e1y, ph\u00e2n t\u00edch th\u1eddi gian th\u1ef1c v\u00e0 t\u1ef1 \u0111\u1ed9ng h\u00f3a trong vi\u1ec7c ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian.<\/p>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi qu\u00e1 tr\u00ecnh ph\u00e2n t\u00e1ch chu\u1ed7i th\u1eddi gian<\/h2>\n<p>C\u00e1c m\u00e1y ch\u1ee7 proxy nh\u01b0 OneProxy c\u00f3 th\u1ec3 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n thu\u1eadn l\u1ee3i cho vi\u1ec7c thu th\u1eadp d\u1eef li\u1ec7u th\u1eddi gian th\u1ef1c \u0111\u1ec3 ph\u00e2n t\u00edch chu\u1ed7i th\u1eddi gian. Ch\u00fang cho ph\u00e9p thu th\u1eadp d\u1eef li\u1ec7u an to\u00e0n v\u00e0 \u1ea9n danh t\u1eeb nhi\u1ec1u ngu\u1ed3n tr\u1ef1c tuy\u1ebfn kh\u00e1c nhau, \u0111\u1ea3m b\u1ea3o b\u1ed9 d\u1eef li\u1ec7u phong ph\u00fa v\u00e0 \u0111a d\u1ea1ng \u0111\u1ec3 ph\u00e2n t\u00edch.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">Trang web OneProxy<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Time_series\" target=\"_new\" rel=\"noopener nofollow\">Ph\u00e2n t\u00edch chu\u1ed7i th\u1eddi gian - Wikipedia<\/a><\/li>\n<li><a href=\"https:\/\/towardsdatascience.com\/introduction-to-time-series-forecasting-30e0ead32c72\" target=\"_new\" rel=\"noopener nofollow\">Gi\u1edbi thi\u1ec7u v\u1ec1 D\u1ef1 b\u00e1o chu\u1ed7i th\u1eddi gian - H\u01b0\u1edbng t\u1edbi khoa h\u1ecdc d\u1eef li\u1ec7u<\/a><\/li>\n<\/ul>\n<p>C\u00e1c li\u00ean k\u1ebft n\u00e0y cung c\u1ea5p nh\u1eefng hi\u1ec3u bi\u1ebft chi ti\u1ebft h\u01a1n v\u1ec1 ph\u00e2n r\u00e3 chu\u1ed7i th\u1eddi gian v\u00e0 c\u00e1c c\u00f4ng ngh\u1ec7 li\u00ean quan.<\/p>","protected":false},"featured_media":470691,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-479331","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Time Series Decomposition<\/mark>","faq_items":[{"question":"What is Time Series Decomposition?","answer":"<p>Time series decomposition is the process of breaking down a time series data set into its constituent parts, typically including trend, seasonal, cyclical, and irregular or random components. Analyzing these components separately can provide valuable insights into the underlying structure of the data.<\/p>"},{"question":"What are the key components of Time Series Decomposition?","answer":"<p>The key components of time series decomposition are the Trend, Seasonal, Cyclical, and Irregular components. The trend shows long-term movements, seasonal reveals repeating patterns, cyclical identifies fluctuations at irregular intervals, and the irregular component accounts for random movements.<\/p>"},{"question":"What are the main types of Time Series Decomposition?","answer":"<p>There are two primary types of time series decomposition: the Additive Model, where components are added together (Trend + Seasonal + Cyclical + Irregular), and the Multiplicative Model, where components are multiplied (Trend \u00d7 Seasonal \u00d7 Cyclical \u00d7 Irregular).<\/p>"},{"question":"How is Time Series Decomposition used in forecasting?","answer":"<p>Time series decomposition is used in forecasting by separating the underlying components of the data. By understanding these components, analysts can make more accurate predictions about future trends and patterns.<\/p>"},{"question":"What problems can be encountered with Time Series Decomposition, and how can they be solved?","answer":"<p>Problems that can be encountered with time series decomposition include overfitting and data quality issues. Overfitting can be avoided by not using overly complex models, and data quality issues can be mitigated by ensuring that the data is clean and well-prepared.<\/p>"},{"question":"What is the relationship between proxy servers like OneProxy and Time Series Decomposition?","answer":"<p>Proxy servers like OneProxy can be associated with time series decomposition by facilitating the collection of real-time data for analysis. They enable secure and anonymous scraping of data from various sources, ensuring a rich and diverse data set for decomposition and analysis.<\/p>"},{"question":"What are the future perspectives related to Time Series Decomposition?","answer":"<p>Future perspectives related to time series decomposition include the integration of machine learning techniques, real-time analysis, and automation. These advancements may lead to more sophisticated and efficient methods for analyzing time series data.<\/p>"},{"question":"How can I learn more about Time Series Decomposition?","answer":"<p>You can learn more about time series decomposition by visiting resources such as the OneProxy website, Wikipedia's page on time series analysis, and various data science blogs and tutorials. The related links section of the article provides direct links to these resources.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/479331","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/479331\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/470691"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=479331"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}