{"id":91103,"date":"2012-02-15T12:00:00","date_gmt":"2012-02-15T11:00:00","guid":{"rendered":"https:\/\/industry-science.com\/artikel\/prediction-of-customer-demands-development-of-a-data-base-containing-recommendations-for-the-choice-of-appropriate-forecasting-methods\/"},"modified":"2025-08-02T11:30:12","modified_gmt":"2025-08-02T09:30:12","slug":"prediction-of-customer-demands-development-of-a-data-base-containing-recommendations-for-the-choice-of-appropriate-forecasting-methods","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/prediction-of-customer-demands-development-of-a-data-base-containing-recommendations-for-the-choice-of-appropriate-forecasting-methods\/","title":{"rendered":"Prediction of Customer Demands"},"content":{"rendered":"<p><!-- GITO PUB shortened content start --><\/p>\n<div class=\"gito-pub-frontend-post-protected\"><\/div>\n<p><!-- GITO PUB shortened content end --><\/p>\n<div style=\"display:block;text-align:center !important;margin:30px 0;\">\n<div style=\"display:inline-block;border:1px solid #555;padding:10px;max-width:600px;text-align:left;\">\n<h2 class=\"gito-pub-download-section\"><center>Access limited<\/center><\/h2>\n<p>You are currently <strong>not logged in \/ not yet registered<\/strong>.<\/p>\n<p>In order to download the desired file(s), you must be logged in and have an appropriate inclusive subscription. 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In order to achieve a well-founded production planning and control, future customer demands have to be predicted precisely. Classical statistical forecasting methods are often easy to apply but are not able to react on dynamic effects within the data. Methods of nonlinear dynamics consider qualitative in addition to quantitative information within past order data to find possible deterministic structures and, as a result, to achieve better forecasts of the future. This article deals with the development of a data base containing recommendations to choose suitable prediction methods in different situations.<\/p>\n","protected":false},"featured_media":97511,"menu_order":0,"template":"","categories":[],"tags":[84279,84280,80214,84281],"product_cat":[3300],"topic":[],"technology":[67717],"knowhow":[],"industry":[],"writer":[80589,82026],"content-type":[],"potential":[],"solution":[],"glossary":[],"class_list":{"0":"post-91103","1":"article","2":"type-article","3":"status-publish","4":"has-post-thumbnail","6":"tag-nonlinear-dynamics-en","7":"tag-prediction-of-customer-demands-en","8":"tag-simulation-en","9":"tag-time-series-analysis-en","10":"product_cat-article","11":"technology-simulation-en","12":"writer-bernd-scholz-reiter-en","13":"writer-mirko-kueck-en","14":"product","15":"first","16":"instock","17":"downloadable","18":"virtual","19":"sold-individually","20":"taxable","21":"purchasable","22":"product-type-article"},"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788.jpg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-150x150.jpg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-666x375.jpg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-768x432.jpg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-1024x576.jpg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-1032x320.jpg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-764x376.jpg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-392x320.jpg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-608x496.jpg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-640x325.jpg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-274x376.jpg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-514x292.jpg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-320x440.jpg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-514x289.jpg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-196x180.jpg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788.jpg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788.jpg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-510x510.jpg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-510x287.jpg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-100x100.jpg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/bsr-kueck_Auswahl-von-prognoseverfahren-fuer-Kundenbedarfe_IM_2012_1-1400x788-64x36.jpg",64,36,true]},"uagb_author_info":{"display_name":"Christoph Brocks","author_link":"https:\/\/industry-science.com\/en\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Due to dynamics and complexity within production and delivery networks, customer demands are often highly volatile. In order to achieve a well-founded production planning and control, future customer demands have to be predicted precisely. Classical statistical forecasting methods are often easy to apply but are not able to react on dynamic effects within the data.&hellip;","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/91103","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media\/97511"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=91103"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=91103"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=91103"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=91103"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=91103"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=91103"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=91103"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=91103"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=91103"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=91103"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=91103"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=91103"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=91103"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}