An Evaluation of Methods for Combining Univariate Time Series Forecasts

This thesis presents and evaluates nineteen methods for combining up to eleven automated univariate forecasts. The evaluation is made by applying the methods on a dataset containing more than 1000 monthly time series. The accuracy of one period ahead forecasts is analyzed. Almost 3.2 million forecasts are evaluated in the study. Methods that are using past forecasts to optimally produce a combined forecast are included, along with methods that do not require this information. A pre-screening procedure to get rid of the poorest performing forecasting methods before the remaining ones are combined is evaluated. The results confirm that it is possible to achieve a superior forecast accuracy by combining forecasts. The best methods that utilize past forecasts tend to outperform the best methods that are not considering this data. Including a pre-screening procedure to remove inferior forecasts before combining forecasts from the top five ranked methods seems to increase the forecast accuracy. The pre-screening procedure consists of ranking the automated univariate forecasting methods using an independent, but relevant, dataset. The four best performing methods utilize the pre-screening procedure together with past forecasts to optimally combine forecasts. The best method computes the historical mean squared error of each individual method and weights them accordingly. Demand for automated procedures is growing as the size of datasets increases within organizations. Forecasting from a large set of time series is an activity that can take advantage of automated procedures. However, choosing which forecasting method to use is often problematic. One way of solving this is by combining multiple forecasts into a single forecast

Mode locking in a spatially extended neuron model: active soma and compartmental tree

Understanding the mode-locked response of excitable systems to periodic forcing has important applications in neuroscience. For example it is known that spatially extended place cells in the hippocampus are driven by the theta rhythm to generate a code conveying information about spatial location. Thus it is important to explore the role of neuronal dendrites in generating the response to periodic current injection. In this paper we pursue this using a compartmental model, with linear dynamics for each compartment, coupled to an active soma model that generates action potentials. By working with the piece-wise linear McKean model for the soma we show how the response of the whole neuron model (soma and dendrites) can be written in closed form. We exploit this to construct a stroboscopic map describing the response of the spatially extended model to periodic forcing. A linear stability analysis of this map, together with a careful treatment of the non-differentiability of the soma model, allows us to construct the Arnol'd tongue structure for 1:q states (one action potential for q cycles of forcing). Importantly we show how the presence of quasi-active membrane in the dendrites can influence the shape of tongues. Direct numerical simulations confirm our theory and further indicate that resonant dendritic membrane can enlarge the windows in parameter space for chaotic behavior. These simulations also show that the spatially extended neuron model responds differently to global as opposed to point forcing. In the former case spatio-temporal patterns of activity within an Arnol'd tongue are standing waves, whilst in the latter they are traveling waves

Friction and Friction Compensation in the Furuta Pendulum

Inverted pendulums are very well suited to investigate friction phenomena and friction compensation because the effects of friction are so clearly noticeable. This paper analyses the effect of friction on the Furuta pendulum. It is shown that friction in the arm drive may cause limit cycles. The limit cycles are well predicted by common friction models. It is also shown that the amplitudes of the limit cycles can be reduced by friction compens ation. Compensators based on the Coulomb friction model and the LuGre model are discussed. Experiments performed show that reduction of the effects of friction can indeed be accomplished

Voluntary Private Investments Role in Pension System in Latvia

Pension systems have become one of the main priorities for the national governments. Developed countries population is getting older by putting the pressure on the state budgets and work age people tax load. The current pension system in Latvia performs according to regulation of state compulsory unfunded pension scheme since 1996 and regulation of the state funded or accumulated pension scheme since 2001. The third pension system pillar is private voluntary pension schemes realized in form of people contributions into pension funds and life insurance policies. Aim of the research – deeper analyses of voluntary private investments as the pension system part and its development challenges in Latvia. Research methods: scientific publications and previous conducted research analysis; analysis of time series on private pension fund developments in Latvia and comparisons with the situation in other OECD countries. The authors were looking for answer on the question – can voluntary private investments cover the gap between pre-retirement and after-retirement income of population in Latvia and what are the pre-conditions for it.The research was supported by the NATIONAL RESEARCH PROGRAMME “LATVIAN HERITAGE AND FUTURE CHALLENGES FOR THE SUSTAINABILITY OF THE STATE” project “CHALLENGES FOR THE LATVIAN STATE AND SOCIETY AND THE SOLUTIONS IN INTERNATIONAL CONTEXT" (INTERFRAME-LV, Project No.VPP-IZM-2018/1-0005

Dynamics of spatially extended dendrites

Dendrites are the most visually striking parts of neurons. Even so many neuron models are of point type and have no representation of space. In this thesis we will look at a range of neuronal models with the common property that we always include spatially extended dendrites. First we generalise Abbott’s “sum-over-trips” framework to include resonant currents. We also look at piece-wise linear (PWL) models and extend them to incorporate spatial structure in the form of dendrites. We look at the analytical construction of orbits for PWL models. By using both analytical and numerical Lyapunov exponent methods we explore phase space and in particular we look at mode-locked solutions. We will then construct the phase response curve (PRC) for a PWL system with compartmentally modelled dendrites. This sets us up so we can look at the effect of multiple PWL systems that are weakly coupled through gap junctions. We also attach a continuous dendrite to a PWL soma and investigate how the position of the gap junction influences network properties. After this we will present a short overview of neuronal plasticity with a special focus on the spatial effects. We also discuss attenuation of distal synaptic input and how this can be countered by dendritic democracy as this will become an integral part of our learning mechanisms. We will examine a number of different learning approaches including the tempotron and spike-time dependent plasticity. Here we will consider Poisson’s equation around a neural membrane. The membrane we focus on has Hodgkin-Huxley dynamics so we can study action potential propagation on the membrane. We present the Green’s function for the case of a one-dimensional membrane in a two-dimensional space. This will allow us to examine the action potential initiation and propagation in a multi-dimensional axon

Model optimization for autotuners in industrial control systems

Automatic tuning of PID controllers using relay feedback experiments has received attention on and off since it was first proposed and industrially implemented in a control system in the 1980s. While optimal experiment design and modern system identification easily outperform the original automatic tuner, they rely on computational resources that are not always available in industrial control systems. Here we present a combination of experiment and subsequent output-error identification of continuoustime first-order time-delayed (FOTD) system models, that requires very little in terms of computations and memory. The method has been extensively evaluated in simulation, and a prototype has been implemented for the ABB AC 800M controller family

Dynamics of spatially extended dendrites

Dendrites are the most visually striking parts of neurons. Even so many neuron models are of point type and have no representation of space. In this thesis we will look at a range of neuronal models with the common property that we always include spatially extended dendrites. First we generalise Abbott’s “sum-over-trips” framework to include resonant currents. We also look at piece-wise linear (PWL) models and extend them to incorporate spatial structure in the form of dendrites. We look at the analytical construction of orbits for PWL models. By using both analytical and numerical Lyapunov exponent methods we explore phase space and in particular we look at mode-locked solutions. We will then construct the phase response curve (PRC) for a PWL system with compartmentally modelled dendrites. This sets us up so we can look at the effect of multiple PWL systems that are weakly coupled through gap junctions. We also attach a continuous dendrite to a PWL soma and investigate how the position of the gap junction influences network properties. After this we will present a short overview of neuronal plasticity with a special focus on the spatial effects. We also discuss attenuation of distal synaptic input and how this can be countered by dendritic democracy as this will become an integral part of our learning mechanisms. We will examine a number of different learning approaches including the tempotron and spike-time dependent plasticity. Here we will consider Poisson’s equation around a neural membrane. The membrane we focus on has Hodgkin-Huxley dynamics so we can study action potential propagation on the membrane. We present the Green’s function for the case of a one-dimensional membrane in a two-dimensional space. This will allow us to examine the action potential initiation and propagation in a multi-dimensional axon

Three HCF Models for Strain Fatigue Life of Welded Pipes in Austenitic Stainless Steel

AbstractFatigue bending tests have been performed on welded pipes made from an austenitic stainless steel. Four types of loading were used: 1) constant amplitude, 2) a load expected at pressure vessel environment, 3) a Gaussian load, and 4) a specially constructed two-level block load. The twenty-eight test results are evaluated using three different models: 1) the classical Basquin equation neglecting the fatigue limit, 2) the ASME model with a fatigue limit, and 3) a model with continuously decreasing fatigue limit. No significant differences between the three models were found. Predictions based on constant amplitude results appear to be non-conservative

Mode locking in a spatially extended neuron model: Active soma and compartmental tree

Understanding the mode-locked response of excitable systems to periodic forcing has important applications in neuroscience. For example, it is known that spatially extended place cells in the hippocampus are driven by the theta rhythm to generate a code conveying information about spatial location. Thus, it is important to explore the role of neuronal dendrites in generating the response to periodic current injection. In this paper we pursue this using a compartmental model, with linear dynamics for each compartment, coupled to an active soma model that generates action potentials. By working with the piecewise linear McKean model for the soma we show how the response of the whole neuron model (soma and dendrites) can be written in closed form. We exploit this to construct a stroboscopic map describing the response of the spatially extended model to periodic forcing. A linear stability analysis of this map, together with a careful treatment of the nondifferentiability of the soma model, allows us to construct the Arnol'd tongue structure for 1:q states (one action potential for q cycles of forcing). Importantly we show how the presence of quasi-active membrane in the dendrites can influence the shape of tongues. Direct numerical simulations confirm our theory and further indicate that resonant dendritic membrane can enlarge the windows in parameter space for chaotic behavior. These simulations also show that the spatially extended neuron model responds differently to global as opposed to point forcing. In the former case spatio-temporal patterns of activity within an Arnol'd tongue are standing waves, whilst in the latter they are traveling waves. © 2009 World Scientific Publishing Company

Fertilisation and irrigation have no effects on growth of oak (Quercus robur, Q. petraea) stands on abandoned farmland in southwest Sweden

Low nutrient availability often limits productivity in northern forests. In a nutrient optimisation trial, we investigated the effects of fertilisation and irrigation on soil moisture, leaf area index (LAI) as well as height and radial growth in 25-year-old stands of pedunculate and sessile oak (Quercus robur L., Q. petraea (Matt.) Liebl.) growing on abandoned farmland in southwestern Sweden. Control (C), fertilisation (F), irrigation (I), and irrigation + fertilisation (IF) treatments were arranged in a randomized complete block design. End of growing season analysis of foliar nutrients guided the quantitative composition of next year's fertiliser mix. Volumetric soil moisture (VWC) was significantly higher in the I and IF treatments compared to the C and F treated stands of both oak species. We did not observe a fertiliser-related reduction in VWC (except for 2015, when VWC in F treated Q. robur stands was significantly lower than the control by about 18 %). This is in line with the unaffected LAI estimates (5.3-5.9) suggesting no stimulation of leaf production that could drive increases in transpiration with subsequent soil moisture depletion. There was no treatment x year interaction for any of the growth-related variables. Treatments had no significant effects on basal area growth, which increased annually by 1.72 and 1.54 m2 ha-1 on average for Q. petraea and Q. robur, respectively. Pre-treatment height differences in Q. petraea stands (7-12 % taller trees in the C and IF plots) persisted throughout the study resulting in significant effects, while no significant differences in height occurred in Q. robur. Periodic annual volume increment varied more strongly following drier periods but there were no significant differences among treatments.Our findings indicate that fertilisation causes no or only minor increases in oak water use, suggesting that nutrient addition in oak stands within this precipitation regime does not require simultaneous irrigation. Most importantly, our data implies that the soil nutrient legacies of past agricultural use suffice to maximise the productivity of oak stands on abandoned farmland typical of the main oak growing region in southwestern Sweden