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This research work presents a systematic investigational study of an interesting challenging phenomenon observed in natural world. Mainly, presented study concerned with conceptual interdisciplinary analysis and evaluation of quantified learning creativity phenomenon. Associated with diverse aspects of measurable behavioral learning performance. That's observed by two diverse natural biological systems'...
Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using different sets of classifiers or using different portions of training/feature sets. Neural networks are often used as base classifiers in multiple classifier systems as they adapt...
Intrusion detection (ID) is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of intrusions, defined as attempts to compromise the confidentiality, integrity, availability, or to bypass the security mechanisms of a computer or network. Internet services, and the number of Internet users increases every day this makes networks as a window for...
The paper presents an upgrading process of rubber tree seed clones identification model using image processing techniques. Sample of rubber tree seeds are captured using digital camera where the RGB color image are processed involving segmentation algorithm which includes thresholding and morphological technique. Texture patterns from seed clones images are then analysed through wavelet's Daubechies...
In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications...
This paper deals with the Fault Detection and Diagnosis of steam boiler using developed artificial Neural networks model. Water low level trip of steam boiler is artificially monitored and analyzed in this study, using two different interpretation algorithms. The Broyden-Fletcher-Goldfarb-Shanno quasi-Newton and Levenberg-Marquart are adopted as training algorithms of the developed neural network...
The use of neural networks as a nonlinear predictor in many applications including predictive image coding has been successfully presented by many researchers. However, almost all of the research papers have focused on the architecture of the neural network and very little attention has been given to the design of the training and testing data. This paper demonstrates how the choice of the training...
Self-healing in systems is one of the main characteristics of Autonomic Computing (AC). In this regard the challenge is how to implement self-healing systems in real time, since online learning is required so that the running system is tuned and adapted automatically, based on the current changes of the system's behavior. In this paper, to overcome the challenges associated with self-healing comprising...
Manufacturing process data collected over time are considered time-series data and can be arranged into control charts. Important applications can be centered around these data like, for example, recognition of specific patterns, pattern similarity, detecting anomalies, and clustering and classification of patterns. We study and evaluate a number of classification techniques for process control data...
This study aimed at identifying the main factors that influence potable water consumption. It was used a neural representation structure to model its consumption, applying geographic and socio-economic variables, as well as TREPAN (trees parroting networks), a special tool to to obtain knowledge from trained artificial neural networks. The model was applied to a database of the State of Parana - Brazil.
In natural world, it is observed that some non-human biological systems show diverse learning aspects. This work presents an interesting comparative study between two naturally inspired learning systems. These are: swarm smarts intelligence for example Ant Colony System (ACS); and behavioural animal learning of Thorndike's cat. The first ACS model used for solving optimally, Traveling Salesman Problem...
Artificial neural networks are highly parallel structures inspired by the human brain. They have been used successfully in many human-like applications, such as pattern recognition. Performance of these networks can be enhanced if used properly in conjunction with equally powerful mathematical tools. In this paper, we used the discrete wavelet transform as a pre-processing tool for two well-known...
This paper presents a new method of analyzing time-frequency plots of heart rate variability to detect sleep disordered breathing from nocturnal ECG. Data is collected from 12 normal subjects (7 males, 5 females; age 46 plusmn 9.38 years, AHI 3.75 plusmn 3.11) and 14 apneic subjects (8 males, 6 females; age 50.28 plusmn 9.60 years; AHI 31.21 plusmn 23.89). The proposed algorithm uses textural features...
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