One of the most important tasks of automatic tool monitoring systems for CNC-lathes is the supervision of a tool's wear. Considering the state of wear and the actual working process (e.g. rough or nish turning) it is possible to exchange a tool (or only the insert) just in time, which o ers signi cant economic advantages. This paper presents a new method to estimate two wear parameters by means...

In a search space of a multilayer perceptron having J hidden units, MLP(J), there exist flat areas called singular regions. Since singular regions cause serious stagnation of learning, a learning method to avoid them was once proposed, but was not guaranteed to find excellent solutions. Recently, SSF1.2 was proposed which utilizes singular regions to stably and successively find excellent solut...

Motivated by the problem of training multilayer perceptrons in neural networks, we consider the problem of minimizing E(x) = ∑ni=1 fi(ξi · x), where ξi ∈ Rs , 1 i n, and each fi(ξi · x) is a ridge function. We show that when n is small the problem of minimizing E can be treated as one of minimizing univariate functions, and we use the gradient algorithms for minimizing E when n is moderately la...

— The shuffle mode, where songs are played in a randomized order that is decided upon for all tracks at once, is widely found and known to exist in music player systems. There are only few music enthusiasts who use this mode since it either is too random to suit their mood or it keeps on repeating the same list every time. In this paper, we propose to build a convolutional deep belief network(C...

This paper considers the similarity between two measures of air pollution/quality control, on the one hand, and widely used indicators of life quality and welfare, on the other. We have developed a multi-layer perceptron neural network system which is trained to predict the measurements of air quality (emissions of sulphur and nitrogen oxides), using Eurostat data for 34 countries. We used life...

The classification of remote sensing images performed with different classifiers usually produces different results. The aim of this paper is to investigate whether the outputs of different soft classifications may be combined to increase the classification accuracy, using the uncertainty information to choose the best class to assign to each pixel. If there is disagreement between the outputs ...

Performance of neural-networks learning is known to be sensitive to the initial weight setting and architecture|number of hidden layers and neurons in these layers. This shortcoming can be alleviated if some approximation of the target concept in terms of a logical description is available. The paper reports a successful attempt to initialize neural networks by decision-tree generators. The sys...

Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will conc...

Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand underestimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep ne...

This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with previously developed weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred games o...