Relevant bibliographies by topics / Orecasting

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  1. Journal articles
  2. Dissertations / Theses

Academic literature on the topic 'Orecasting'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Orecasting"

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IBRAHIM, Abdullahı Abdu, and Khalıd Mohamed Abdullah ELZARIDI. "XGBOOST ALGORITHM FOR ORECASTING ELECTRICITY CONSUMPTION OF GERMANY." AURUM Journal of Engineering Systems and Architecture 7, no. 1 (2023): 99–108. http://dx.doi.org/10.53600/ajesa.1321195.

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Stability requires energy demand prediction. We train and test 24-hour German load forecasting models. ENTSO-E Transparency Platform data covered European energy generation, transmission, and consumption. It uses German load data instead of PJM data for the eastern US, adds holidays and lag features to the XGB model, and benchmarks with a linear model and a random forest. Grid search CV refines the final XGB model. National load forecasting RMSE is 1740MW, which is suitable for the gradient boosting model. H-24 and H-48 lag is the most important for this job. Weekends and holidays help, but le
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Djaby, Bakary, Allard De Wit, Louis Kouadio, Moussa El Jarroudi, and Bernard Tychon. "Spatial Distribution of Calibrated WOFOST Parameters and Their Influence on the Performances of a Regional Yield orecasting System." Sustainable Agriculture Research 2, no. 4 (2013): 12. http://dx.doi.org/10.5539/sar.v2n4p12.

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We investigate in this study (i) a redefinition of crop variety zonations at a spatial scale of 10x10 km, and (ii) the influence of recalibrated crop parameters on regional yield forecasting of winter wheat and grain maize in western Europe. The baseline zonation and initial crop parameter set was derived from the operational European crop growth monitoring system (CGMS) which involves the agrometeorological model WOFOST. Air temperature data from 325 weather stations over the 1992-2007 period were used to define new zonations in a 300 x 300 km test site. Two parameters which influenced mostly
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Sivalingam, Kumar Chandar, Sumathi Mahendran, and Sivanandam Natarajan. "Forecasting Gold Prices Based on Extreme Learning Machine." International Journal of Computers Communications & Control 11, no. 3 (2016): 372. http://dx.doi.org/10.15837/ijccc.2016.3.2009.

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<p>In recent years, the investors pay major attention to invest in gold market ecause of huge profits in the future. Gold is the only commodity which maintains ts value even in the economic and financial crisis. Also, the gold prices are closely elated with other commodities. The future gold price prediction becomes the warning ystem for the investors due to unforeseen risk in the market. Hence, an accurate gold rice forecasting is required to foresee the business trends. This paper concentrates on orecasting the future gold prices from four commodities like historical data’s of gold ric
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Jizhong燴hu, Yuwang燤iao, Hanjiang燚ong, Shenglin燣i, Ziyu燙hen та Di燴hang. "Short-term燫esidential燣oad燜orecasting燘ased爋n K-shape燙lustering燼nd燚omain燗dversarial燭ransfer燦etwork". Journal of Modern Power Systems and Clean Energy 12, № 4 (2024): 1239–49. http://dx.doi.org/10.35833/mpce.2023.000646.

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Dolgikh, E. A., and T. V. Kudryashova. "FORECASTING INFLATION AT THE REGIONAL LEVEL IN THE SHORT TERM USING A VECTOR AUTOREGRESSION MODEL." Beneficium, no. 2 (2023): 41–56. http://dx.doi.org/10.34680/beneficium.2023.2(47).41-56.

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The paper presents the stages of constructing a vector autoregression model (VAR model) for forecasting inflation at the regional level and implements a short-term inflation forecast for the Novgorod region. For this purpose, the selection of possible indicators (20 units) for the VAR model was carried out, the need for their use was economically justified. As a result, 4 indicators were used for the VAR model. The explanatory variables included the following ones: Price indices of producers of agricultural products sold by agricultural organizations (products and services of agriculture and h
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Saputra, Roni, Said Sunardiyo, Anan Nugroho, and Subiyanto Subiyanto. "Implementasi Multilayer Perceptron Artificial Neural Network untuk Prediksi Konsumsi Energi Listrik PT PLN (Persero) UP3 Salatiga." Elektrika 15, no. 2 (2023): 60. http://dx.doi.org/10.26623/elektrika.v15i2.6411.

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<p class="Text"><em>Electricity is energy that flows through cable networks and has become an important part of the progress of human civilization in various fields. The high demand for electrical energy for consumers requires providers of electrical energy to provide a reliable but economical supply of electrical energy. Therefore, strategies and methods are needed to adjust the supply and demand of electrical energy. This can be achieved by carrying out proper and appropriate operational planning. One of the important steps in planning the operation of an electric power system is
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Garside, Annisa Kesy. "Perencanaan Kanabn Card Controller (KCC) dalam Pengendalian Tingakt Produksi Guna Meminimalisasi Kekurangan dan Kelebihan Produksi." Jurnal Teknik Industri 1, no. 1 (2010): 20. http://dx.doi.org/10.22219/jtiumm.vol1.no1.20-30.

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This research asa im to planK anbanC ontrolC ard( KCC) in productionra te controllingsomep roductsa s : Ofiice Table( MTK), TowerC hestF ourF lours( TC-4),ToweCr hestS ix Flours(TC-6), Simple Table (MD).In this research we need data such as : production demand data history, production leadtime, demandf orecastinga nd productiond atab asef rom demandh istory ( 25 weeklyp eriodic),thenf orecasdt emandin periodic2 6 d'usingT ime seriesm ethodw ith TrendA nalysisi n a secondperiodic.UsingM RP logic, forecastingre sulta ccounto resultP lanedO rderR elease(P ORs)f oreachw ork stationF. romt he dataa
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Ifa yuliana, Murti Astuti. "Penyusunan Jadwal Induk Industri dengan Menggunakan Metode Simpleks Guna Meminimalkan Biaya Produksi." Jurnal Teknik Industri 2, no. 2 (2010): 86. http://dx.doi.org/10.22219/jtiumm.vol2.no2.86-95.

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PT. IndustriS andanNg usantaraP atalS ecangM agelangis somef actoryt hat regardinginmanufactur sector which thread producting. For this time the factory have a problem with stackingsamek ind of producta ndi n the otherw ay lessa notherp roduct.T his casec auseth at factoryu seproducts chedulinbga sedo n experiencaen dr eckonedo fselling in lastp eriod.c onnectedw ith thisproblem,t he casei s how to make a good schedulein order that factory could be completingconsumedr emanda ndd ecideds omem ainp roducts chedulwe ith simpleksm ethode.The articulatein factoryf or thist ime is regulere mployee6
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"Ecology and Epidemiology in R: Disease F​orecasting and Validation." Plant Health Instructor, 2008. http://dx.doi.org/10.1094/phi-a-2008-0129-05.

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Kryvorychko, І. А., N. M. Goncharova та O. V. Arsenуev. "Прогнозування вибору методу оперативного втручання при ускладнених псевдокістах підшлункової залози третього типу = Forecasting method of choice of surgical intervention in complicated pancreatic pseudocysts third type". 2 червня 2016. https://doi.org/10.5281/zenodo.54600.

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<strong>Kryvorychko</strong> <strong>І.</strong> <strong>А., </strong><strong>Goncharova N</strong><strong>.</strong> <strong>M</strong><strong>., </strong><strong>Arsen</strong><strong>у</strong><strong>ev O</strong><strong>.</strong> <strong>V</strong><strong>. Прогнозування вибору методу оперативного втручання при ускладнених псевдокістах підшлункової залози третього типу</strong><strong> = </strong><strong>F</strong><strong>orecasting method of choice of surgical intervention in complicated pancreatic pseudocysts third type. </strong><strong>Journal of Education, Health and Sport. 2016;6(6
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Dissertations / Theses on the topic "Orecasting"

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Крамаренко, Семен Віталійович. "Прогнозування електроспоживання на базі вейвлетів". Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2019. https://ela.kpi.ua/handle/123456789/28917.

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Сучасні тенденції на ринку електроніки вимагають пошуку комплексних рішень по прогнозуванні електроспоживання локальних об’єктів. Тому, є актуальним дослідження методів, які при мінімальних розрахунках будуть проводити прогнозування з максимальною точністю. У дипломній роботі були досліджені існуючи методи прогнозування електроспоживання локального об’єкту. Було з’ясовано, що на сьогоднішній день існує два основні методи прогнозування електроспоживання, які передбачають ситуацію з істотними стрибками електроспоживання, а саме: метод прогнозування електроспоживання за допомогою нейронни
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Хозієв, Л. "Шляхи підвищення конкурентоспроможності підприємства (на прикладі дистриб'юторської компанії)". Thesis, Одеський національний економічний університет, 2020. http://dspace.oneu.edu.ua/jspui/handle/123456789/12435.

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У роботі розглядаються теоретичні аспекти конкурентоспроможності підприємства. Визначено сутність поняття конкуренції і конкурентоспроможності підприємства. Наведено методи оцінки та фактори конкурентоспроможності підприємства. Проаналізовано фінансово-господарську діяльність ТОВ «Блейд». Проведено оцінку рівня та резервів підвищення конкурентоспроможності підприємства. Запропоновано економічне обґрунтування шляхів підвищення конкурентоспроможності ТОВ «Блейд».<br>The paper considers the theoretical aspects of enterprise competitiveness. The essence of the concept of competition and competit
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