Search results for: Extended Park´s vector approach

Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

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In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.

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Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design.

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Authors: Gheorghe Galben, Daniel N. Aloi

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Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.

Keywords: Autonomous navigation, extended kalman filter, unscented kalman filter, localization algorithms.

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: Biomass concentration, Extended Kalman Filter, Particle Filter, State estimation, Specific growth rate.

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Authors: Jongho Park, Taekyun Kim, Jungbhin You, Sungnam Hong, Sun-Kyu Park

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Due to the aging of bridges, increasing of maintenance costs and decreasing of structural safety is occurred. The steel corrosion of reinforced concrete bridge is the most common problem and this phenomenon is accelerating due to abnormal weather and increasing CO₂ concentration due to climate change. To solve these problems, composite members using textile have been studied. A textile reinforced concrete can reduce carbon emissions by reduced concrete and without steel bars, so a lot of structural behavior studies are needed. Therefore, in this study, textile reinforced concrete beam was made and flexural test was performed. Also, the change of flexural strength according to the prestressing was conducted. As a result, flexural strength of TRC with prestressing was increased compared and flexural behavior was shown as reinforced concrete.

Keywords: AR-glass, flexural strength, prestressing, textile reinforced concrete.

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Authors: Susanta Banerjee, Sanjaya Kumar Patro

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Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.

Keywords: Floating column, Infill Wall, Park-Ang Damage Index, Damage State.

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Authors: Pandian Elavarasan, Kishore Kondamudi, Sreedevi Upadhyayula

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Ionic liquids are well known as green solvents, reaction media and catalysis. Here, three different sulfonic acid functional ionic liquids prepared in the laboratory are used as catalysts in alkylation of p-cresol with tert-butyl alcohol. The kinetics on each of the catalysts was compared and a kinetic model was developed based on the product distribution over these catalysts. The kinetic parameters were estimated using Marquadt's algorithm to minimize the error function. The Arrhenius plots show a curvature which is best interpreted by the extended Arrhenius equation.

Keywords: Alkylation, p-cresol, tert-butyl alcohol, kinetics, activation parameter, extended Arrhenius equation.

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Authors: Ji Hyeong Park, Ji Hye Jeon, Hyo Seon Park

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Environmental pollution problems have been globally main concern in all fields including economy, society and culture into the 21st century. Beginning with the Kyoto Protocol, the reduction on the emissions of greenhouse gas such as CO2 and SOX has been a principal challenge of our day. As most buildings unlike durable goods in other industries have a characteristic and long life cycle, they consume energy in quantity and emit much CO2. Thus, for green building construction, more research is needed to reduce the CO2 emissions at each stage in the life cycle. However, recent studies are focused on the use and maintenance phase. Also, there is a lack of research on the initial design stage, especially the structure design. Therefore, in this study, we propose an optimal design plan considering CO2 emissions and cost in composite buildings simultaneously by applying to the structural design of actual building.

Keywords: Multi-objective optimization, CO2 emissions, structural cost, encased composite structure

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Authors: Sungho Kim, Chaehoon Park, Yukyung Choi, Soon Kwon, In So Kweon

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In this paper, a novel corner detection method is presented to stably extract geometrically important corners. Intensity-based corner detectors such as the Harris corner can detect corners in noisy environments but has inaccurate corner position and misses the corners of obtuse angles. Edge-based corner detectors such as Curvature Scale Space can detect structural corners but show unstable corner detection due to incomplete edge detection in noisy environments. The proposed image-based direct curvature estimation can overcome limitations in both inaccurate structural corner detection of the Harris corner detector (intensity-based) and the unstable corner detection of Curvature Scale Space caused by incomplete edge detection. Various experimental results validate the robustness of the proposed method.

Keywords: Feature, intensity, contour, hybrid.

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Authors: L.A du Plessis

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South Africa is facing a crisis with not being able to produce enough graduates in the scarce skills areas to sustain economic growth. The crisis is fuelled by a school system that does not produce enough potential students with Mathematics, Accounting and Science. Since the introduction of the new school curriculum in 2008, there is no longer an option to take pure maths on a standard grade level. Instead, only two mathematical subjects are offered: pure maths (which is on par with higher grade maths) and mathematical literacy. It is compulsory to take one or the other. As a result, lees student finishes Grade 12 with pure mathematics every year. This national problem needs urgent attention if South Africa is to make any headway in critical skills development as mathematics is a gateway to scarce skills professions. Higher education institutions initiated several initiatives in an attempt to address the above, including preparatory courses, bridging programmes and extended curricula with foundation provisions. In view of the above, and government policy directives to broaden access in the scarce skills areas to increase student throughput, foundation provision was introduced for Commerce and Information Technology programmes at the Vaal Triangle Campus (VTC) of North-West University (NWU) in 2010. Students enrolling for extended programmes do not comply with the minimum prerequisites for the normal programmes. The question then arises as to whether these programmes have the intended impact? This paper reports the results of a two year longitudinal study, tracking the first year academic achievement of the two cohorts of enrolments since 2010. The results provide valuable insight into the structuring of an extended programme and its potential impact.

Keywords: Access, extended programmes, foundation provision, mathematics.

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Authors: Shuzhen Yao, Fengjing Zhao, Jianwei He

Abstract:

The UML modeling of complex distributed systems often is a great challenge due to the large amount of parallel real-time operating components. In this paper the problems of verification of such systems are discussed. ECPN, an Extended Colored Petri Net is defined to formally describe state transitions of components and interactions among components. The relationship between sequence diagrams and Free Choice Petri Nets is investigated. Free Choice Petri Net theory helps verifying the liveness of sequence diagrams. By converting sequence diagrams to ECPNs and then comparing behaviors of sequence diagram ECPNs and statecharts, the consistency among models is analyzed. Finally, a verification process for an example model is demonstrated.

Keywords: Consistency, liveness, Petri Net, sequence diagram.

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Authors: ML. Benmessaoud, A. Lamrani, K. Nemra, AK. Souici

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This paper presents an Extended Kaman Filter implementation of a single-camera Visual Simultaneous Localization and Mapping algorithm, a novel algorithm for simultaneous localization and mapping problem widely studied in mobile robotics field. The algorithm is vision and odometry-based, The odometry data is incremental, and therefore it will accumulate error over time, since the robot may slip or may be lifted, consequently if the odometry is used alone we can not accurately estimate the robot position, in this paper we show that a combination of odometry and visual landmark via the extended Kalman filter can improve the robot position estimate. We use a Pioneer II robot and motorized pan tilt camera models to implement the algorithm.

Keywords: Mobile Robot, Navigation, vSLAM, EKF, monocular.

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Authors: T. Thendral, M. S. Vijaya, S. Karpagavalli

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Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.

Keywords: Classification, Feature extraction, Support vector machine, Training, Writer.

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Authors: T. Thendral, M. S. Vijaya, S. Karpagavalli

Abstract:

Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.

Keywords: Classification, Feature extraction, Support vector machine, Training, Writer.

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Authors: Seong-Bae Park, Sang-Soo Kim, Sewook Oh, Zooyl Zeong, Hojin Lee, Seong Rae Park

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An ontology is widely used in many kinds of applications as a knowledge representation tool for domain knowledge. However, even though an ontology schema is well prepared by domain experts, it is tedious and cost-intensive to add instances into the ontology. The most confident and trust-worthy way to add instances into the ontology is to gather instances from tables in the related Web pages. In automatic populating of instances, the primary task is to find the most proper concept among all possible concepts within the ontology for a given table. This paper proposes a novel method for this problem by defining the similarity between the table and the concept using the overlap of their properties. According to a series of experiments, the proposed method achieves 76.98% of accuracy. This implies that the proposed method is a plausible way for automatic ontology population from Web tables.

Keywords: Ontology population, domain knowledge consolidation, target concept selection, property overlap.

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Authors: Ick Hoon Jang, Hoon Jae Lee, Dae Hoon Kwon, Ui Young Pak

Abstract:

In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

Keywords: BDIP, BVLC, FFT, language identification, texture feature, wavelet transform.

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Authors: Khadija Raissi, Bechir Ben Gouissem

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In this paper, we perform the investigation of some routing protocols in Vehicular Ad-Hoc Network (VANET) context. Indeed, we study the efficiency of protocols like Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector Routing (AODV), Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing convention (OLSR) and Vehicular Multi-hop algorithm for Stable Clustering (VMASC) in terms of packet delivery ratio (PDR) and throughput. The performance evaluation and comparison between the studied protocols shows that the VMASC is the best protocols regarding fast data transmission and link stability in VANETs. The validation of all results is done by the NS3 simulator.

Keywords: VANET, smart city, AODV, OLSR, DSR, OLSR, VMASC, routing protocols, NS3.

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Authors: Jungbhin You, Taekyun Kim, Jongho Park, Sungnam Hong, Sun-Kyu Park

Abstract:

Reinforced concrete has been mainly used in construction field because of excellent durability. However, it may lead to reduction of durability and safety due to corrosion of reinforcement steels according to damage of concrete surface. Recently, research of textile is ongoing to complement weakness of reinforced concrete. In previous research, only experiment of longitudinal length were performed. Therefore, in order to investigate the adhesion performance according to the lattice shape and the embedded length, the pull-out test was performed on the roving with parameter of the number of lateral reinforcement, the lateral reinforcement length and the lateral reinforcement spacing. As a result, the number of lateral reinforcement and the lateral reinforcement length did not significantly affect the load variation depending on the adhesion performance, and only the load analysis results according to the reinforcement spacing are affected.

Keywords: Adhesion performance, lateral reinforcement, pull-out test, textile.

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Authors: Gilberto Gonzalez-A

Abstract:

Bond graph models of an electrical transformer including the nonlinear saturation are presented. These models determine the relation between self and mutual inductances, and the leakage and magnetizing inductances of power transformers with two and three windings using the properties of a bond graph. The modelling and analysis using this methodology to three phase power transformers or transformers with internal incipient faults can be extended.

Keywords: Bond graph, electrical transformer, nonlinear saturation

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution neural network, edges, face recognition, support vector machine.

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Authors: Khodamorad Nabaki, Jianhu Shen, Xiaodong Huang

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This paper develops a method for considering the critical fatigue stress as a constraint in the Bi-directional Evolutionary Structural Optimization (BESO) method. Our aim is to reach an optimal design in which high cycle fatigue failure does not occur for a specific life time. The critical fatigue stress is calculated based on modified Goodman criteria and used as a stress constraint in our topology optimization problem. Since fatigue generally does not occur for compressive stresses, we use the p-norm approach of the stress measurement that considers the highest tensile principal stress in each point as stress measure to calculate the sensitivity numbers. The BESO method has been extended to minimize volume an object subjected to the critical fatigue stress constraint. The optimization results are compared with the results from the compliance minimization problem which shows clearly the merits of our newly developed approach.

Keywords: Topology optimization, BESO method, p-norm, fatigue constraint.

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Authors: Rehab F. Abdel-Kader, Rabab M. Ramadan, Rawya Y. Rizk

Abstract:

The recognition of human faces, especially those with different orientations is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation invariant face recognition using Log-Polar Transform and Discrete Cosine Transform combined features. The rotation invariant feature extraction for a given face image involves applying the logpolar transform to eliminate the rotation effect and to produce a row shifted log-polar image. The discrete cosine transform is then applied to eliminate the row shift effect and to generate the low-dimensional feature vector. A PSO-based feature selection algorithm is utilized to search the feature vector space for the optimal feature subset. Evolution is driven by a fitness function defined in terms of maximizing the between-class separation (scatter index). Experimental results, based on the ORL face database using testing data sets for images with different orientations; show that the proposed system outperforms other face recognition methods. The overall recognition rate for the rotated test images being 97%, demonstrating that the extracted feature vector is an effective rotation invariant feature set with minimal set of selected features.

Keywords: Discrete Cosine Transform, Face Recognition, Feature Extraction, Log Polar Transform, Particle SwarmOptimization.

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Authors: I.Banerjee, A.K.Mahendra, T.K.Bera, B.G.Chandresh

Abstract:

The scroll pump belongs to the category of positive displacement pump can be used for continuous pumping of gases at low pressure apart from general vacuum application. The shape of volume occupied by the gas moves and deforms continuously as the spiral orbits. To capture flow features in such domain where mesh deformation varies with time in a complicated manner, mesh less solver was found to be very useful. Least Squares Kinetic Upwind Method (LSKUM) is a kinetic theory based mesh free Euler solver working on arbitrary distribution of points. Here upwind is enforced in molecular level based on kinetic flux vector splitting scheme (KFVS). In the present study we extended the LSKUM to moving node viscous flow application. This new code LSKUM-NS-MN for moving node viscous flow is validated for standard airfoil pitching test case. Simulation performed for flow through scroll pump using LSKUM-NS-MN code agrees well with the experimental pumping speed data.

Keywords: Least Squares, Moving node, Pitching, Spirals.

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Authors: R. Saraçoğlu, N. Allahverdi

Abstract:

Searching similar documents and document management subjects have important place in text mining. One of the most important parts of similar document research studies is the process of classifying or clustering the documents. In this study, a similar document search approach that includes discussion of out the case of belonging to multiple categories (multiple categories problem) has been carried. The proposed method that based on Fuzzy Similarity Classification (FSC) has been compared with Rocchio algorithm and naive Bayes method which are widely used in text mining. Empirical results show that the proposed method is quite successful and can be applied effectively. For the second stage, multiple categories vector method based on information of categories regarding to frequency of being seen together has been used. Empirical results show that achievement is increased almost two times, when proposed method is compared with classical approach.

Keywords: Document similarity, Fuzzy classification, Multiple categories, Text mining.

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Authors: J.E. Park, G.R. Kim, D.J. Yoon, C.H. Sin, I.S. Park, T.S. Bea, M.H. Lee

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Carbon nanotubes (CNTs) are attractive because of their excellent chemical durability mechanical strength and electrical properties. Therefore there is interest in CNTs for not only electrical and mechanical application, but also biological and medical application. In this study, the dispersion power of surfactant-treated multiwalled carbon nanotubes (MWCNTs) and their effect on the antibacterial activity were examined. Surfactant was used sodium dodecyl-benzenesulfonate (SDBS). UV-vis absorbance and transmission electron microscopy(TEM) were used to characterize the dispersion of MWCNTs in the aqueous phase, showing that the surfactant molecules had been adsorbed onto the MWCNTs surface. The surfactant-treated MWCNTs exhibited antimicrobial activities to streptococcus mutans. The optical density growth curves and viable cell number determined by the plating method suggested that the antimicrobial activity of surfactant-treated MWCNTs was both concentration and treatment time-dependent.

Keywords: MWCNT, SDBS, surfactant, antibacterial.

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Authors: Stanislovas Buteliauskas, Aušrius Juozapavičius

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City road transport contributes significantly to climate change, and the ongoing world urbanization is only increasing the problem. The paper describes a city planning concept minimizing the number of vehicles on the roads while increasing overall mobility. This becomes possible by utilizing a recently invented two-level road junction with a unique property of serving both as an intersection of uninterrupted traffic and an easily accessible transport hub capable of accumulating private vehicles, and therefore becoming an especially effective park-and-ride solution, and a logistics or business center. Optimized layouts of city road infrastructure, living and work areas, and major roads are presented. The layouts are suitable both for the development of new cities as well as for the expansion of existing ones. Costs of the infrastructure and a positive impact on climate are evaluated in comparison to current city growth patterns.

Keywords: Congestion, city infrastructure, park-and-ride, road junctions.

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

Abstract:

Aging infrastructures became a serious social problem. This brought out the increased need for the legislation of a new strict guideline for infrastructure management. Although existing guidelines provided basics of how to evaluate and manage the condition of infrastructures, they needed improvements for their evaluation procedures. Most guidelines mainly focused on the structural condition of infrastructures and did not properly reflect service aspects of infrastructures such as performance, public demand, capacity, etc., which were significantly valuable to public. Regardless of the importance, these factors were often neglected in infrastructure evaluations, because they were quite subjective and difficult to quantify in rational manner. Thus, this study proposed a framework to properly identify and evaluate the service indicators. This study showed that service indicators could be grouped into two categories and properly evaluated using AHP and Fuzzy. Overall, proposed framework is expected to assist governmental agency in establishing effective investment strategies for infrastructure improvements.

Keywords: Infrastructure, evaluation, serviceability, fuzzy.

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Authors: Rohit Choudhry, Kumkum Garg

Abstract:

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators. The results show that the hybrid GA-SVM system outperforms the stand alone SVM system.

Keywords: Genetic Algorithms, Support Vector Machines, Stock Market Forecasting.

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Authors: K. Benamrane, T. Abdelkrim, T. Benslimane, Aeh. Benkhelifa, B. Bezza

Abstract:

This paper presents a comparison between two Pulse Width Modulation (PWM) algorithms applied to a three-level Neutral Point Clamped (NPC) Voltage Source Inverter (VSI). The first algorithm applied is the triangular-sinusoidal strategy; the second is the Space Vector Pulse Width Modulation (SVPWM) strategy. In the first part, we present a topology of three-level NCP VSI. After that, we develop the two PWM strategies to control this converter. At the end the experimental results are presented.

Keywords: Multilevel inverter, Space vector pulse width modulation (SVPWM), triangular-sinusoidal strategy.

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