Bio-Inspired Applications of Connectionism

rozdział

A Thermocouple Model Based on Neural Networks

Nicolás Medrano-Marqués, Rafael -Hoyo-Alonso, Bonifacio Martín-del-Brío

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 531-538

Thermocouples are temperature sensors of common use in industrial applications. Classical mathematical models for these sensors consist of a set of two to four polynomial expressions reproducing their behaviour in different temperature ranges. In this work we propose a new ‘one stage’ model for these sensors covering the whole sensing range. The modelization has been carried out with an artificial...

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Improving Biological Sequence Property Distances by Using a Genetic Algorithm

Olga M. Perez1, F. J. Marin, O. Trelles

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 539-546

In this work we present a genetic-algorithm-based approach to optimise weighted distance measurements from compositional and physical-chemical properties of biological sequences that allow a significant reduction of the computational cost associated to the distance evaluation, while maintaining a high accuracy when comparing with traditional methodologies. The strategy has a generic and parametric...

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Data Mining Applied to Irrigation Water Management

Juan A. Botía, Antonio F. Gómez-Skarmeta, Mercedes Valdés, Antonio Padilla

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 547-554

This work addresses the application of data mining to obtain artificial neural network based models for the application in water management during crops irrigation. This problem is very important in the zone of the South-East of Spain, as there is an important lack of rainfall there. These intelligent analysis techniques are used in order to optimize the consumption of such an appreciated and limited...

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Classification of Specular Object Based on Statistical Learning Theory

Tae Soo Yun

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 555-562

This paper has presented an efficient solder joint inspection technique through the use of wavelet transform and Support Vector Machines. The proposed scheme consists of two stages: a feature extraction stage for extracting features with wavelet transform, and a classification stage for classifying solder joints with a support vector machines. Experimental results show that the proposed method produces...

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On the Application of Heteroassociative Morphological Memories to Face Localization

B. Raducanu, M. Graña

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 563-570

Face localization is a previous step for face recognition and in some circumstances has proven to be a difficult task. The Heteroassociative Morphological Memories are a recently proposed neural network architecture based on the shift of the basic algebraic framework. They possess some robustness to specific noise models (erosive and dilative noise). Here we show how they can be applied to the task...

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Early Detection and Diagnosis of Faults in an AC Motor Using Neuro Fuzzy Techniques: FasArt + Fuzzy k Nearest Neighbors

J. Juez, G. I. Sainz, E. J. Moya, J. R. Perán

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 571-578

An approach to detect and to classify incipient faults in an AC motor is introduced in this paper. This approach is based in an ART based neuro fuzzy system, (FasArt Fuzzy Adaptive System ART based), and in the fuzzy k nearest neighbor algorithm that is employing in an auxiliary way to complete the learning set. A set of 15 non destructive faults has been tested and both a high degree of early...

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Knowledge-Based Neural Networks for Modelling Time Series

Jacobus Zyl, Christian W. Omlin

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 579-586

Various methods exist for extracting rules from data for classification purposes. We propose a new method for initializing a neural network used for time series modelling and prediction. We extract binary rules from a real valued time series and encode them into a neural network using an adaptation of KBANN. We test the method on the Lorenz system as well as on real world data in the form of a seismic...

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Using Artificial Neural Network to Define Fuzzy Comparators in FSQL with the Criterion of some Decision Maker

R. Carrasco, J. Galindo, A. Vila

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 587-594

At present we have a FSQL server available for Oracle© Databases, programmed in PL/SQL. This server allows us to query a Fuzzy or Classical Database with the FSQL language (Fuzzy SQL). The FSQL language is an extension of the SQL language which permits us to write flexible (or fuzzy) conditions in our queries to a fuzzy or traditional database. In this paper we have incorporated a method of ranking...

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Predictive Classification for Integrated Pest Management by Clustering in NN Output Space

M. Salmerón, D. Guidotti, R. Petacchi, L. M. Reyneri

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 595-602

In this paper we consider the successful hybridation of a two modern computational schemes, Clustering and Neural Networks, for the Predictive Classification of the future value of insect infestation levels for Integrated Pest Management (IPM) of olive groves. The predictive classification techniques employed allow managers to improve their work in two ways: first, by reducing sampling demands of...

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Blind Source Separation in the Frequency Domain: A Novel Solution to the Amplitude and the Permutation Indeterminacies

Adriana Dapena, Luis Castedo

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 603-610

This paper deals with the separation of convolutive mixtures of statistically independent signals (sources) in the frequency domain. The convolutive mixture is decomposed in several problems of separating instantaneous mixtures which are independently solved. In addition, we propose a method to remove the indeterminacies which occur when all the individual separating systems do not extract the sources...

rozdział

Evaluation, Classification and Clustering with NeuroFuzzy Techniques in Integrate Pest Management

E. Bellei, D. Guidotti, R. Petacchi, L. M. Reyneri, więcej

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 611-618

In the present article are described the results obtained by the application of neuro-fuzzy methodologies in the study of Bactrocera Oleae (olive fly) infestation in Liguria region olive grows. The main aim of this project is create an informatic decisional support for experts in the applications of Integrated Pest Management strategies against the Bactrocera Oleae infestation. This system...

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Inaccessible Parameters Monitoring in Industrial Environment: A Neural Based Approach

Kurosh Madani, Ion Berechet

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 619-627

In the case of a large number of applications, especially complex industrial ones, the knowledge on system’s (process, plant, etc.) parameters during the operation of the system is of major importance. However, in real cases, there are always parameters, which are not accessible. In the present work, we focus our interest around the extraction possibility of information relative to inaccessible parameters...

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Autoorganised Structures for Extraction of Perceptual Primitives

Marta Penas, María J. Carreira, Manuel G. Penedo

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 628-635

In this work we have used directional features extracted from Gabor wavelet responses to compare different auto-organised networks in order to extract perceptual primitives without taking into account the kind of images to analyse. This is an adequate problem to prove the performance of these models because of the high dimensionality of the input space. Three different models have been analysed: self-organised...

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Real-Time Wavelet Transform for Image Processing on the Cellular Neural Network Universal Machine

Victor M. Preciado

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 636-643

A novel algorithm for achieving Wavelet transform on the Cellular Neural Network Universal Machine (CNN-UM) visual neuroprocessor is presented in this work. The CNN-UM is implemented on a VLSI programmable chip having real time and supercomputer power. This neurocomputer is a large scale nonlinear analog circuit made of a massive aggregate of regularly spaced neurons which communicate with each other...

rozdział

OBLIC: Classification System Using Evolutionary Algorithm

J. L. Alvarez, J. Mata, J. C. Riquelme

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 644-651

We present a new classification system based on Evolutionary Algorithm (EA), OBLIC. This tool is an OBLIque Classification system whose function is to induce a set of classification rules no hierarchical from a database or training set. The core of the algorithm is a EA with real-coded and Pittsburgh approach. Each individual is composed by a no fixed classification rules set what split in regions...

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Design of a Pre-processing Stage for a voiding the Dependence on TSNR of a Neural Radar Detector

Pilar Jarabo Amores, Manuel Rosa Zurera, Francisco López Ferreras

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 652-659

A new pre-processing stage for neural radar detectors is presented in order to reduce the detector performance dependence on the Training Signal-to-Noise Ratio (TSNR). The proposed scheme combines Time-frequency Analysis for transforming radar echoes into a feature space where the detection task is easier, and Principal Component Analysis for dimensionality reduction. The results are compared with...

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Foetal Age and Weight Determination Using a Lateral Interaction Inspired Net

A. Fernández-Caballero, J. Mira, F. J. Gómez, M. A. Fernández

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 660-670

The clinical estimate of the foetal weight is probably one of the most difficult parameters to obtain in the prenatal control. Only very accurate foetal body measurements reflect the gestation age and the weight of the foetus. A model is presented that performs an automated foetal age and weight determination from ultrasound by means of biparietal diameter, femur lenght and abdominal circumference...

rozdział

Inference of Stochastic Regular Languages through Simple Recurrent Networks with Time Delays

Gustavo A. Casañ, M. Asunción Castaño

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 671-678

Previous work in the literature has shown that, using a local representation of the alphabet, simple recurrent neural networks were able to estimate the probability distribution corresponding to strings which belong to a stochastic regular language. This paper carries on with the empirical works in the matter by including input time delays in simple recurrent networks. This technique could sometimes...

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Is Neural Network a Reliable Forecaster on Earth? A MARS Query!

Ajith Abraham, Dan Steinberg

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 679-686

Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear phenomena in nature exhibiting what is known as the “butterfly effect”. While some regions of the world are noticing a systematic decrease in annual rainfall, others notice increases in flooding...

rozdział

Character Feature Extraction Using Polygonal Projection Sweep (Contour Detection)

Roberto J. Rodrigues, Gizelle K. Vianna, Antonio C. G. Thomé

Lecture Notes in Computer Science > Bio-Inspired Applications of Connectionism > General Applications > 687-695

It is presented in this paper a new approach to the problem of feature extraction. The approach is based on the edge detection, where a set of feature vectors is taken from the source image. The images under this investigation are considered to be manuscript characters and the features are obtained by the distance from the contour of each character to several observation points placed around the image...

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Bio-Inspired Applications of Connectionism
6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001 Proceedings, Part II

A Thermocouple Model Based on Neural Networks

Improving Biological Sequence Property Distances by Using a Genetic Algorithm

Data Mining Applied to Irrigation Water Management

Classification of Specular Object Based on Statistical Learning Theory

On the Application of Heteroassociative Morphological Memories to Face Localization

Early Detection and Diagnosis of Faults in an AC Motor Using Neuro Fuzzy Techniques: FasArt + Fuzzy k Nearest Neighbors

Knowledge-Based Neural Networks for Modelling Time Series

Using Artificial Neural Network to Define Fuzzy Comparators in FSQL with the Criterion of some Decision Maker

Predictive Classification for Integrated Pest Management by Clustering in NN Output Space

Blind Source Separation in the Frequency Domain: A Novel Solution to the Amplitude and the Permutation Indeterminacies

Evaluation, Classification and Clustering with NeuroFuzzy Techniques in Integrate Pest Management

Inaccessible Parameters Monitoring in Industrial Environment: A Neural Based Approach

Autoorganised Structures for Extraction of Perceptual Primitives

Real-Time Wavelet Transform for Image Processing on the Cellular Neural Network Universal Machine

OBLIC: Classification System Using Evolutionary Algorithm

Design of a Pre-processing Stage for a voiding the Dependence on TSNR of a Neural Radar Detector

Foetal Age and Weight Determination Using a Lateral Interaction Inspired Net

Inference of Stochastic Regular Languages through Simple Recurrent Networks with Time Delays

Is Neural Network a Reliable Forecaster on Earth? A MARS Query!

Character Feature Extraction Using Polygonal Projection Sweep (Contour Detection)

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Bio-Inspired Applications of Connectionism
6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001 Proceedings, Part II