Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Is it possible to utilize VIX for a profitable trading strategy of S&P 500 Index?

The goal of this research was to make an overall sight to VIX® and how it can be used as a stock market indicator. Volatility index often referred as the fear index, measures how much it costs for investor to protect his/her S&P 500 position from fluctuations with options. Over the relatively short history of VIX it has been a successful timing coordinator and it has given incremental information about the market state adding its own psychological view of the amount of fear and greed. Correctly utilized VIX information gives a considerable advantage in timing market actions. In this paper we test how VIX works as a leading indicator of broad stock market index such as S&P 500 (SPX). The purpose of this paper is to find a working way to interpret VIX. The various tests are made on time series data ranging from the year 1990 to the year 2010. The 10-day simple moving average strategy gave significant profits from the whole time when VIX data is available. Strategy was able to utilize the increases of SPX in example portfolio value and was able to step aside when SPX was declining. At the times when portfolio was aside of S it was on safety fund like on treasury bills getting an annual yield of 3 percent. On the other side just a static number’s of VIX did not work as indicators in a profit making way.

A tour through Sweden, Swedish-Lapland, Finland and Denmark. In a series of letters, illustrated with engravings : by Matthew Consett, esq.

P. 143-158 are misnumbered 142-157.

Hiilijalanjäljen laskenta ISO 14064-1 -standardin ja PAS 2050 -ohjeen mukaisesti. Case: Metsähallitus Laatumaa

Tämän kandidaatintyö on osa Laatumaan kestävän kehityksen periaatteiden määrittämisprojektia ja sen tarkoituksena on tuottaa tietoa toiminnan ilmastovaikutuksista, edesauttaa päästövähennys- ja kompensaatiotavoitteita sekä edistää ympäristötietoutta yrityksen sisällä. Työssä tarkastellaan SFS-ISO 14064-1 -standardin sekä PAS 2050 -ohjeistuksen asettamia hiilijalanjäljen laskennan laatuvaatimuksia sekä selvitetään Laatumaan toiminnan ilmastovaikutusta standardiin pohjautuvan kasvihuonekaasuinventaarion kautta.

Iso kirja aseena

Kirjallisuusarvostelu

The world & ourselves

kuv., 14 x 21 cm

Nash Standard Six series

kuv., 24 x 18 cm

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Iso-Britannian panssarijoukkojen käyttöperiaatteiden kehittyminen kylmän sodan aikana

Tutkimus käsittelee Iso-Britannian asevoimien panssarijoukkojen käyttöperiaatteiden kehittymistä kylmän sodan aikana. Tutkimuksen tavoitteena on selvittää miten Iso-Britannian doktriinin muutos kylmän sodan aikana on vaikuttanut panssarijoukkojen käyttöperiaatteiden kehittymiseen. Perushypoteesina tutkimuksessa on, että uhkakuvien muutos on saanut aikaan muutostarpeen doktriiniin. Tämä taas on asettanut uudet vaatimukset panssarijoukkojen käyttöperiaatteille osana maavoimien suunniteltua käyttöä. Aihetta lähestytään asiakirja- ja kirjallisuustutkimuksen menetelmin vertailemalla Iso-Britannian ja Naton doktriinin muutoksia käsitteleviä teoksia sekä panssarijoukkoja ja niiden käyttöä käsittelevää kirjallisuutta. Tutkimuksessa ilmeni, että Naton ja Iso-Britannian doktriinin muutos on muuttanut panssarijoukkojen käyttöperiaatteita. Toisen maailmansodan jälkeen brittien kahtiajakautunut ajattelutapa panssarivaunujen käyttöperiaatteista hidasti panssarijoukkojen kootun tai liikesodankäyntiin perustuvan käytön kehittämistä. 1950- ja 1960-luvuilla doktriini asetti panssarijoukoille vaatimuksen kyvystä toimia ydinsodassa. Selkeimmin tämä näkyi panssarivaunun teknisessä kehityksessä. 1970-luvulla panssarijoukkojen käyttöperiaatteet päivittyivät uuden doktriinin vaatimuksista entistä liikkuvimmiksi. 1980-luvulle sijoittuivat merkittävimmät kylmän sodan aikaiset panssarijoukkojen käyttöperiaatteiden muutokset. Uusi doktriini perustui liikesodankäynnin periaatteisiin ja asetti joukkojen joustavan käytön etusijalle. Käytännössä tämä näkyi panssaridivisioonien muodostamien taisteluryhmien ja -osastoiden käytössä. Panssarijoukkojen joustavammalla käytöllä Keski-Euroopassa uskottiin vastattavan paremmin Neuvostoliiton syvän taistelun periaatteisiin perustuvaan hyökkäykseen.