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The World Conference on Complex Systems (WCCS) has become one of the most relevant events in the study of real systems. This second conference (WCCS 2014) is co-organized by Ibn Zohr University and Moroccan Society of Complex Systems in partnership with IEEE Morocco and the sponsorship of the International Academy for Systems and Cybernetic Science IASCYS.
We propose a machine learning method for breast cancer data analysis and classification, based on support vector machines (SVM) and particle swarm optimization (PSO). This method uses SVM as a model for supervised learning with the goal of minimizing generalization errors, and PSO as an optimization technique for automatic determination of the best values of two algorithmic parameters of SVM. Its...
In this paper, we propose a new approach to deal with the high rate of false alarms generated by the health monitoring system (HMS). It consists of an intelligent alarm algorithm based on a new version of the support vector machines (SVM). Actually, medical staff face many issues when using the current HMS in intensive care unit (ICU). This latter generates a large number of alarms due to the exceed...
Handwritten digit recognition is an active topic in optical character recognition applications and pattern learning research. However, the extraction of informative features from handwritten digits for recognition task remains the most important step for achieving high accuracy. This work investigates the effectiveness of four feature extraction approaches based on Discrete Cosine Transform (DCT)...
P300 is one of the most studied and used event related potentials (ERP) in brain computer interfaces (BCI). The classical oddball paradigm is usually used to evoke the P300 from Electroencephalogram (EEG) signals. However, EEG raw data are noisy which make the P300 detection very difficult. In this paper, we aim to detect the P300 wave as accurate as possible using appropriate feature extraction method...
Sparse matrices are entailed in many linear algebra problems such as linear systems resolution, matrix eigen-values/vectors computation and partial differential equations, wherefore sparse matrix vector product (SpMV) constitutes a basic kernel for solving many scientific and engineering applications problems. With the appearance of Graphics Processing Units (GPUs) as platforms that provides important...
Bat algorithm (BA) is a new nature-inspired metaheuristic optimization algorithm based on the echolocation behavior of bats to find their prey and to avoid obstacles in the darkness. This new algorithm has showed a higher efficiency in solving continuous optimization problems. In this study, we have proposed a novel adaptation of BA for solving travelling salesman problem (TSP), which is known as...
This paper proposes an approach to computer network as a complex system that has some level of self-organization where interactions between nodes result in a diverse set of emergent behaviors. The work analyzes artificial computational model of neural networks in order to help us to understand the dynamics of a complex system, and to show their remarkably flexible ability to capture a variety of behaviors...
Case-Based Reasoning (CBR) is considered a fundamental modality in Computational Intelligence; It has the ability to accumulate previous cases records of particular past reasoning experiences and retrieve and adjust them in order to help new problem-solving in related situations. Undesirably, this incremental store process causes the uncontrolled case base growth. This mess distresses the competence...
Existing methods dealing with the problem of rank aggregation in the context of meta-search in information retrieval are considered as a passive learner machine and suffer in the presence of unreliable ranking lists. This paper proposes a novel approach which selects the most informative features and instances to be labeled from which the model will learn. To train an efficient ranking aggregation...
This paper proposes a new uncertain metaclustering approach devoted for handling uncertainty in the belonging of objects to different clusters with respect to their membership values. These values are presented under possibilistic framework to deal with uncertainty when an object belongs to several clusters. In addition, we use the meta-clustering which is based on the k-modes method to double-cluster...
This work relates to SQL query plan reuse based optimization in Database Management Systems (DBMS). We use a collaborative recommendation approach that helps the DBMS optimizer to detect similarity between old queries (already executed by the optimizer) and new upcoming queries (that are yet to execute). This kind of methods, allows the optimizer to use the old access plans to execute future queries...
This paper presents the nonlinear control of single-phase grid connected to the photovoltaic system through an adaptation circuit and LCL filter. The control objective is threefold i) regulating the DC voltage to a desired value (VR) ii) supply a current with sinusoidal form and in phase with the grid voltage by controlling DC/AC converter (power factor correction: PFC) iii) extracting the maximum...
The aim of this paper is to present interesting results obtained by implementing big data classification algorithm using a cooperative mobile agents model. In this work we focused on the application of this classification for Magnetic Resonance Images (MRI) segmentation which is presented based on parallel fine grained c-means algorithm. This algorithm is converged to distributed classification c-means...
Anesthesia is a branch of medical science generally applied to patients who need surgery or painful acts. Research in this field has brought many changes by decreasing the mortality rate that is why in this work, we propose a computer aided diagnosis system based on Support Vector Machines (SVM) aiming to help doctors in the pre-anesthetic examination. For that, a new database has been obtained with...
Supply chain management (SCM) is an emerging field that has commanded attention from different communities. On the one hand, the optimization of supply chain which is an important issue, requires a reliable prediction of future demand. On the other hand, It has been shown that intelligent systems and machine learning techniques are useful for forecasting in several applied domains. In this paper,...
Optical Character Recognition (OCR) is a process that allows converting scanned or photographed images of typewritten or printed text into editable text. The OCR studies have been explored towards many languages. However, there are not many reliable OCR systems available for the Amazigh language. Furthermore, the existed studies focus only on Tifinagh writing system, an alphabet that has been recently...
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