The multi-section transport conveyor model based on the neural network for predicting the output flow parameters is considered. The expediency of using sequential and batch modes of training of a neural network in a model of a multi-section transport conveyor has been investigated. The quality...

We introduce two neural network models designed for application in statistical learning. The mean-variance neural network regression model allows us to simultaneously model the mean and the variance of a response variable. In case of a two-dimensional response vector, the...

The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical...

The Lee-Carter model is a basic approach to forecasting mortality rates of a single population. Although extensions of the Lee-Carter model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are...

The aim of this project is to analyse high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, braking and changes of direction from this high-frequency GPS location data. Time series of this feature...

We present an actuarial loss reserving technique that takes into account both claim counts and claim amounts. Separate (over-dispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural...

Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the ``error maximization'' problem where inaccuracy in parameter estimation...

This paper introduces the MCTS algorithm to the financial world and focuses on solving significant multi-period financial planning models by combining a Monte Carlo Tree Search algorithm with a deep neural network. The MCTS provides an advanced start for the neural network so that the combined...

In this paper, a model of a transport conveyor system using a neural network is demonstrated. The analysis of the main parameters of modern conveyor systems is presented. The main models of the conveyor section, which are used for the design of control systems for flow parameters, are...

The owner of a mortgage can decide to repay his loan before the contractual maturity, completely or in part, in most cases without suffering any penalty. This might happen for a number of reasons which can go even beyond market driven incentives - ie. a more favourable general level of interest...