Short-term forecasting of power demand in the Nord Pool market

Sähkönkulutuksen lyhyen aikavälin ennustamista on tutkittu jo pitkään. Pohjoismaisien sähkömarkkinoiden vapautuminen on vaikuttanut sähkönkulutuksen ennustamiseen. Aluksi työssä perehdyttiin aiheeseen liittyvään kirjallisuuteen. Sähkönkulutuksen käyttäytymistä tutkittiin eri aikoina. Lämpötila tilastojen käyttökelpoisuutta arvioitiin sähkönkulutusennustetta ajatellen. Kulutus ennusteet tehtiin tunneittain ja ennustejaksona käytettiin yhtä viikkoa. Työssä tutkittiin sähkönkulutuksen- ja lämpötiladatan saatavuutta ja laatua Nord Poolin markkina-alueelta. Syötettävien tietojen ominaisuudet vaikuttavat tunnittaiseen sähkönkulutuksen ennustamiseen. Sähkönkulutuksen ennustamista varten mallinnettiin kaksi lähestymistapaa. Testattavina malleina käytettiin regressiomallia ja autoregressiivistä mallia (autoregressive model, ARX). Mallien parametrit estimoitiin pienimmän neliösumman menetelmällä. Tulokset osoittavat että kulutus- ja lämpötiladata on tarkastettava jälkikäteen koska reaaliaikaisen syötetietojen laatu on huonoa. Lämpötila vaikuttaa kulutukseen talvella, mutta se voidaan jättää huomiotta kesäkaudella. Regressiomalli on vakaampi kuin ARX malli. Regressiomallin virhetermi voidaan mallintaa aikasarjamallia hyväksikäyttäen.

Wireless e-Business Applications - Methods for Forecasting the Demand of Wireless Services and Technologies

Tämä tutkimus oli osa sähköistä liiketoimintaa ja langattomia sovelluksia tutkivaa projektia ja tutkimuksen tavoitteena oli selvittää ennustamisen rooli päätöksenteko- ja suunnitteluprosessissa ja määrittää parhaiten soveltuvat ja useimmin käytetyt teknologian ennustusmenetelmät. Ennustusmenetelmiä tarkasteltiin erityisesti uuden teknologian ja pitkän aikavälin ennustamisen näkökulmasta. Tutkimus perustui teknologista ennustamista, pitkän aikavälin suunnittelua ja innovaatioprosesseja käsittelevän kirjallisuuden analysointiin. Materiaalin perusteella kuvataan teknologian ennustamista informaation hankkimisvälineenä organisaatioiden suunnitteluprosessin apuna. Työssä arvioidaan myös seuraavat teknologisen ennustamisen menetelmät: trendianalyysi-, Delfoi-, cross-impact analyysi-, morfologinen analyysi- ja skenaario analyysimenetelmä. Työ tuo esille jokaisen ennustusmenetelmä ominaispiirteet, rajoitukset ja sovellusmahdollisuudet. Käyttäen esiteltyjä menetelmiä, saadaan kerättyä hyödyllistä informaatiota tulevaisuuden näkymistä, joita sitten voidaan käyttää hyväksi organisaatioiden suunnitteluprosesseissa.

Factors Affecting the Forecasting Accuracy of Diffusion Models

Tutkielman tavoitteena oli tarkastella innovaatioiden leviämismallien ennustetarkkuuteen vaikuttavia tekijöitä. Tutkielmassa ennustettiin logistisella mallilla matkapuhelinliittymien leviämistä kolmessa Euroopan maassa: Suomessa, Ranskassa ja Kreikassa. Teoriaosa keskittyi innovaatioiden leviämisen ennustamiseen leviämismallien avulla. Erityisesti painotettiin mallien ennustuskykyä ja niiden käytettävyyttä eri tilanteissa. Empiirisessä osassa keskityttiin ennustamiseen logistisella leviämismallilla, joka kalibroitiin eri tavoin koostetuilla aikasarjoilla. Näin tehtyjä ennusteita tarkasteltiin tiedon kokoamistasojen vaikutusten selvittämiseksi. Tutkimusasetelma oli empiirinen, mikä sisälsi logistisen leviämismallin ennustetarkkuuden tutkimista otosdatan kokoamistasoa muunnellen. Leviämismalliin syötettävä data voidaan kerätä kuukausittain ja operaattorikohtaisesti vaikuttamatta ennustetarkkuuteen. Dataan on sisällytettävä leviämiskäyrän käännöskohta, eli pitkän aikavälin huippukysyntäpiste.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Surgically-treated Hip Fracture in older People. With Special Emphasis on Mortality Analysis

Hip fractures are associated with significant morbidity and mortality. Cervical and trochanteric fractures have a different morphometry, surgical treatment, and outcome. Polypharmacy, common in older people, is associated with increased mortality. The risk factors for mortality can be identified based on cause-of-death analysis. In this population-based study, 461 older, surgically in 1999-2000 treated hip fracture patients were enrolled. Incidence, morphometry, medication, mortality, and cause-of-death were analysed. Hip fractures were most commonly sustained by women, occurred mostly indoors, and often in institutions. One in four patients had sustained a previous fracture. Routine clinical radiographs revealed no differences in the hip geometry between hip fracture types. Age-adjusted mortality was higher in men than in women during the follow-up. Chronic lung disease and male sex were predictors of mortality after cervical fracture. In men, potent anticholinergics were associated with excess age-adjusted mortality. Men were more likely to die from circulatory disease and dementia after hip fracture than women. Mortality after hip fracture was 3-fold higher than that of the general population, including every cause-of-death class. Fracture prevention in institutions and homes, indoor safety measures, and treatment of chronic lung diseases should be encouraged. Hip morphometry analyses require more accurate measures than that provided by routine radiographs. Careful use of potent anticholinergics may reduce mortality. Compared to the general population, excess mortality after hip fracture was evident up to 9 years after hip fracture. Cause-of-death analysis indicates that all major comorbidities require optimal treatment after hip fracture surgery.

Effects of Socioeconomic Status and Sociodemographic Features on Cardiovascular Disease. Mortality and Morbidity in Finland

Despite declining trends in morbidity and mortality, cardiovascular diseases have a considerable impact on Finnish public health. A goal in Finnish health policy is to reduce inequalities in health and mortality among population groups. The aim of this study was to assess inequalities in cardiovascular diseases according to socioeconomic status (SES), language groups and other sociodemographic characteristics. The main data source was generated from events in 35-99 year-old men and women registered in the population-based FINMONICA and FINAMI myocardial infarction registers during the years ranging from 1988-2002. Information on population group characteristics was obtained from Statistics Finland. Additional data were derived from the FINMONICA and FINSTROKE stroke registers and the FINRISK Study. SES, measured by income level, was a major determinant of acute coronary syndrome (ACS) mortality. Among middle-aged men, the 28-day mortality rate of the lowest group of six income groups was 5.2 times and incidence 2.7 times as high when compared to the highest income group. Among women, the differences were even larger. Among the unmarried, the incidence of ACS was approximately 1.6 times as high and their prognosis was significantly worse than among married persons - both in men and women and independent of age. Higher age-standardized attack rates of ACS and stroke were found among Finnish-speaking compared to Swedish-speaking men in Turku and these differences could not be completely explained by SES. In these language groups, modest differences were found in traditional risk factor levels possibly explaining part of the found morbidity and mortality inequality. In conclusion, there are considerable differences in the morbidity and mortality of ACS and stroke between socioeconomic and sociodemographic groups, in Finland. Focusing measures to reduce the excess morbidity and mortality, in groups at high risk, could decrease the economic burden of cardiovascular diseases and thus be an important public health goal in Finland.