Search results for " class"
showing 10 items of 3720 documents
Soil genetic erosion: New conceptual developments in soil security
2019
In the last decades, in some Mediterranean areas, pedodiversity decreased mainly due to pedotechnique application in large-scale farming that transformed original soils into Anthrosols. Supporting the consideration that soils can be considered as living systems, the original concept of 'soil genetic erosion' is re-proposed. Data, extrapolated and modeled from a Soil Information System in a study case representative of a Mediterranean landscape, predicted that most of the soil types would disappear in few years leading to a decrease of the soil diversity and originating soil genetic erosion. This circumstance is intentionally here told in form of a story where the fairy tale characters are s…
Introducing a Fuzzy-Pattern Operator in Fuzzy Time Series
2017
In this paper we introduce a fuzzy pattern operator and propose a new weighting fuzzy time series strategy for generating accurate ex-post forecasts. A decision support system is built for managing the weights of the information provided by the historical data, under a fuzzy time series framework. Our procedure analyzes the historical performance of the time series using different experiments, and it classifies the characteristics of the series through a fuzzy operator, providing a trapezoidal fuzzy number as one-step ahead forecast. We also present some numerical results related to the predictive performance of our procedure with time series of financial data sets.
Darboux integrable system with a triple point and pseudo-abelian integrals
2016
We study pseudo-abelian integrals associated with polynomial perturbations of Dar-boux integrable system with a triple point. Under some assumptions we prove the local boundedness of the number of their zeros. Assuming that this is the only non-genericity, we prove that the number of zeros of the corresponding pseudo-abelian integrals is bounded uniformly for nearby Darboux integrable foliations.
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…
Adjusted bat algorithm for tuning of support vector machine parameters
2016
Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…
P-FCM: a proximity-based fuzzy clustering for user-centered web applications
2003
Abstract In last years, the Internet and the web have been evolved in an astonishing way. Standard web search services play an important role as useful tools for the Internet community even though they suffer from a certain difficulty. The web continues its growth, making the reliability of Internet-based information and retrieval systems more complex. Nevertheless there has been a substantial analysis of the gap between the expected information and the returned information, the work of web search engine is still very hard. There are different problems concerning web searching activity, one among these falls in the query phase. Each engine provide an interface which the user is forced to le…
An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery
2018
This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…
Political interest furthers partisanship in England, Scotland, and Wales
2016
ABSTRACTAccording to much of the literature, partisanship in Britain exercises little independent influence on the vote but merely reflects voters’ prospective and retrospective evaluations of the parties’ performance with regard to their management of the economy, national security, and public services. In this view, partisanship comes close to Fiorina’s model of a “running tally” of political experiences. Similarly, Dalton’s notion of “cognitive mobilization” suggests that seeking out political information should undermine both the need for and the likelihood of party identification. Applying Mixed Markov Latent Class Analysis to the British Election Study Panel 1997–2000, we challenge th…
A risk assessment proposal for underground cavities in Hard Soils-Soft Rocks
2018
Abstract Underground calcarenite quarries in Marsala (Sicily) have been involved in a number of collapses that have, seriously damaged numerous buildings. The stability conditions were therefore examined in order to assess risk conditions within the historical centre of the town and the surrounding areas, which are subject to urban expansion. Starting with an extensive collection of historical information, the research was carried out through surveys of the cavities, systematic sampling of material, petrographic analysis and geotechnical testing. The results of laboratory tests and in situ investigations provided a geotechnical characterization of both the intact material and the rock mass.…
Image-Evoked Affect and its Impact on Eeg-Based Biometrics
2019
Electroencephalography (EEG) signals provide a representation of the brain’s activity patterns and have been recently exploited for user identification and authentication due to their uniqueness and their robustness to interception and artificial replication. Nevertheless, such signals are commonly affected by the individual’s emotional state. In this work, we examine the use of images as stimulus for acquiring EEG signals and study whether the use of images that evoke similar emotional responses leads to higher identification accuracy compared to images that evoke different emotional responses. Results show that identification accuracy increases when the system is trained with EEG recordin…