A queueing problem in pattern recognition
A rainfall forecasting method using machine learning models and its application to the Fukuoka city case
In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid multi-model...
A Reconstruction of Digital Parabolas from Their Least Squares Fit Representation
A reduction-based theorem prover for 3-valued logic.
We present a new prover for propositional 3-valued logics, TAS-M3, which is an extension of the TAS-D prover for classical propositional logic. TAS-M3 uses the TAS methodology and, consequently, it is a reduction-based method. Thus, its power is based on the reductions of the size of the formula executed by the F transformation. This transformation dynamically filters the information contained in the syntactic structure of the formula to avoid as much distributions as possible, in order to improve...
A Revision about the Concept of Intentionality in an Approximate Framework.
A rough set-based knowledge discovery process
The knowledge discovery from real-life databases is a multi-phase process consisting of numerous steps, including attribute selection, discretization of real-valued attributes, and rule induction. In the paper, we discuss a rule discovery process that is based on rough set theory. The core of the process is a soft hybrid induction system called the Generalized Distribution Table and Rough Set System (GDT-RS) for discovering classification rules from databases with uncertain and incomplete data....
A rule based machine learning approach to the nonlinear multifingered robot gripper problem
A scratch removal method
We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.
A selection-based formal description of an environment
A Semi-Topological Classification of the Line Figures
A short note on Perez’s approximation by dependence structure simplification
Perez’s approximations of probability distributions by dependence structure simplification were introduced in 1970s, much earlier than graphical Markov models. In this paper we will recall these Perez’s models, formalize the notion of a compatible system of elementary simplifications and show the necessary and sufficient conditions a system must fulfill to be compatible. For this we will utilize the apparatus of compositional models.
A simple upper bound to the Bayes error probability for feature selection
In this paper, feature selection in multiclass cases for classification of remote-sensing images is addressed. A criterion based on a simple upper bound to the error probability of the Bayes classifier for the minimum error is proposed. This criterion has the advantage of selecting features having a link with the error probability with a low computational load. Experiments have been carried out in order to compare the performances provided by the proposed criterion with the ones of some of the widely...
A Single Period Inventory Model of a Deteriorating Item Sold from Two Shops With Shortage Via Genetic Algorithm
A stochastic approach to robot plan formation
A strategy learning model for autonomous agents based on classification
In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation...
A survey of factors influencing MLP error surface
A survey of methods to evaluate quantified sentences.
The evaluation of quantified sentences is used to solve several problems. Most of the methods proposed in the literature are not satisfactory because they do not verify some intuitive properties. In this paper we propose an extension of both possibilistic and probabilistic methods, based on the Sugeno and the Choquet fuzzy integrals respectively, for the evaluation of type II sentences, the most general kind of sentences. These methods verify good properties, and they are shown to be better than...
A synchronization property of pure subsemigroups.
A syntactic characterization of bounded-rank decision trees in terms of decision lists
A technique for dynamically measuring and modifying relevance while problem solving.