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The complex regimes of operation situated between ordered and chaotic behavior are hypothesized to give rise to computational capabilities. Lacking an universal blueprint for the emergence of complexity, a costly search is typically used to find the configurations of distributed artificial systems that can facilitate global computation. In this paper, we address the tedious task of searching for complex...
Vehicle Ad hoc Network (VANET) provides an opportunity for innovation in the transportation area, enabling services for Intelligent Transportation System (ITS). Because of VANET features, such as highly dynamic networks topology and frequent discontinuity, it is desirable to establish, at a given moment, routes for fast delivery of messages, having a low probability of disconnection. This leads to...
Neural assembly computing (NAC) is a framework for investigating computational operations realized by spiking cell assemblies and for designing spiking neural machines. NAC concerns the way assemblies interact and how it results in information processing with causal and hierarchical relations. In addition, NAC investigates how assemblies represent states of the world, how they control data flux carried...
In this article a number of neural networks based on self organizing maps, that can be successfully used for dynamic object identification, is described. The structure and algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results is given.
Currently managing information overload has become a major challenge. How to manage all these data, presented in diverse formats and originating from heterogeneous sources? This paper presents a strategy to perform data fusion effectively. Our strategy deals with the problem of object identification in the context of the Command and Control of the Brazilian Defense Ministry using MIP Data Model from...
Tracking of multiple bright particles (spots) in fluorescence microscopy image sequences is seen as a crucial step in understanding complex information in the cell. However, fluorescence microscopy generates high a volume of noisy image data that cannot be analysed efficiently by means of manual analysis. In this study we compare the performance of two computer-based tracking methods for tracking...
In this paper, we propose a new methodology based on the Negative Selection Algorithm that belongs to the field of Computational Intelligence (specifically, Artificial Immune Systems - AIS) to identify takeover targets. Although considerable research based on customary statistical techniques and some contemporary Computational Intelligence techniques have been devoted to identify takeover targets,...
In this paper, we propose a comparative analysis of the use of cryptography and transformation functions to be used as biometric (signature) template protection methods. The main goal is to investigate the increasement of the biometric dataset security as well as the performance of the protected dataset in the biometric-based systems. We use the well-elaborated structures for pattern recognition (ensembles...
Researchers have been challenged to combine time series forecasting models, with the intention of enhancing forecast accuracy and efficiency. In this way, to weight models accuracy, efficiency, and mutual dependency becomes paramount. A promising way to address this issue is via copulas. Copulas are joint probability distribution functions aimed to envelop both the marginal distribution as well as...
Extended Kalman Filter (EKF) is a method widely used for noise treatment in robotics systems. It needs to perform several computational operations such as matrix multiplication, matrix inversions and Jacobians. In Fast SLAM, a solution for SLAM (Simultaneous Localization and Mapping) problem, EKF is utilized for landmarks updates. SLAM should be solved in real time. Artificial neural networks can...
Considering the importance of monitoring pipeline systems, this work presents the development of a technique to detect gas leakage in pipelines, based on acoustic method and on-line prediction of leak location using neural artificial networks. Audible noises generated by leakage were captured by a microphone installed in a 60 m long pipeline. The sound noises were decomposed into sounds of different...
Modeling of reasoning in intelligent systems on the example of intelligent decision support system of real time by means of integration of methods based on case-based reasoning (accumulated experience) and inductive notion formation in the presence of noisy data are considered.
Particle Swarm Optimization (PSO) is an evolutionary heuristics-based method used for continuous function optimization. Compared to existing stochastic methods, PSO is very robust. Nevertheless, for real-world optimizations, it requires a high computational effort. In general, parallel implementations of PSO provide better performance. However, this depends heavily on the parallelization strategy...
Opt Bees is an algorithm inspired by the processes of collective decision-making by bee colonies designed with the objective of generating and maintaining diversity, trading off exploitation (diversification) and exploration (intensification) and promoting a multimodal search, so that a broader coverage of promising regions of the search space can be achieved, allowing the determination of locally...
This work delves into variations of FSS that uses local information (i.e. fish weights) for splitting the school and presents comparative analyses of the new method, tried here in three ways. Hence, this is an attempt to create a more economical alternative for the best performing multimodal version of the algorithm FSS, the dFSS. The work capitalizes on some modifications in the Collective Instinctive...
Particle swarm optimization (PSO) is an iterative algorithm, where particle positions and best positions are updated per iteration. The order in which particle positions and best positions are updated is referred to in this paper as an iteration strategy. Two main iteration strategies exist for PSO, namely synchronous updates and asynchronous updates. A number of studies have discussed the advantages...
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