Search results for: Particle Swarm Optimization algorithm

Authors: Jiashang Jiang, Yongxin Yuan

Abstract:

In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.

Keywords: Model updating, damped gyroscopic system, partially prescribed spectral information.

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Authors: M. S. Agha, A. M. Eshahiry, S. A. Aldabbar, Z. M. Alshahri

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The propagation of microwave is affected by rain and dust particles causing signal attenuation and de-polarization. Computations of these effects require knowledge of the propagation characteristics of microwave and millimeter wave energy in the climate conditions of the studied region. This paper presents effect of wind and humidity on wireless communication such as microwave links in the North West region of Libya (Al-Khoms). The experimental procedure is done on three selected antennae towers (Nagaza station, Al-Khoms center station, Al-Khoms gateway station) for determining the attenuation loss per unit length and cross-polarization discrimination (XPD) change. Dust particles are collected along the region of the study, to measure the particle size distribution (PSD), calculate the concentration, and chemically analyze the contents, then the dielectric constant can be calculated. The results show that humidity and dust, antenna height and the visibility affect both attenuation and phase shift; in which, a few considerations must be taken into account in the communication power budget.

Keywords: Attenuation, scattering, transmission loss.

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Authors: Z. Abdullah, A. R. Hamdan

Abstract:

Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the area in data mining and it can be classified into partition, hierarchical, density based and grid based. Therefore, in this paper we do survey and review four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems as well as deriving more robust and scalable algorithms for clustering.

Keywords: Clustering, method, algorithm, hierarchical, survey.

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Authors: Hyung Suk Kang

Abstract:

A triangular fin with variable fin base thickness is analyzed and optimized using a two-dimensional analytical method. The influence of fin base height and fin base thickness on the temperature in the fin is listed. For the fixed fin volumes, the maximum heat loss, the corresponding optimum fin effectiveness, fin base height and fin tip length as a function of the fin base thickness, convection characteristic number and dimensionless fin volume are represented. One of the results shows that the optimum heat loss increases whereas the corresponding optimum fin effectiveness decreases with the increase of fin volume.

Keywords: A triangular fin, Convection characteristic number, Heat loss, Fin base thickness.

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Authors: K. Noah, F.-S. Lien

Abstract:

In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: Compressible lattice Boltzmann metho-, large eddy simulation, turbulent jet flows.

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Authors: Aneeqa Sabah, Saadat Anwar Siddiqi, Salamat Ali

Abstract:

The systematic manipulations of shapes and sizes of inorganic compounds greatly benefit the various application fields including optics, magnetic, electronics, catalysis and medicine. However shape control has been much more difficult to achieve. Hence exploration of novel method for the preparation of differently shaped nanoparticles is challenging research area. II-VI group of semiconductor cadmium sulphide (CdS) nanostructure with different morphologies (such as, acicular like, mesoporous, spherical shapes) and of crystallite sizes vary from 11 to 16 nm were successfully synthesized by chemical aqueous precipitation of Cd2+ ions with homogeneously released S2- ions from decomposition of cadmium sulphate (CdSO4) and thioacetamide (CH3CSNH2) by annealing at different radiations (microwave, ultrasonic and sunlight) with matter and systematic research has been done for various factors affecting the controlled growth rate of CdS nanoparticles. The obtained nanomaterials have been characterized by X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Thermogravometric (DSC-TGA) analysis and Scanning Electron Microscopy (SEM). The result indicates that on increasing the reaction time particle size increases but on increasing the molar ratios grain size decreases.

Keywords: CdS nanoparticles, Morphology, Oxidation, Radiations

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Authors: B. Farhadinia

Abstract:

Although so far, many methods for ranking fuzzy numbers have been discussed broadly, most of them contained some shortcomings, such as requirement of complicated calculations, inconsistency with human intuition and indiscrimination. The motivation of this study is to develop a model for ranking fuzzy numbers based on the lexicographical ordering which provides decision-makers with a simple and efficient algorithm to generate an ordering founded on a precedence. The main emphasis here is put on the ease of use and reliability. The effectiveness of the proposed method is finally demonstrated by including a comprehensive comparing different ranking methods with the present one.

Keywords: Ranking fuzzy numbers, Lexicographical ordering.

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Authors: M. Raseen, A.Assi, P.W. C. Prasad, A. Harb

Abstract:

Binary Decision Diagrams (BDDs) are useful data structures for symbolic Boolean manipulations. BDDs are used in many tasks in VLSI/CAD, such as equivalence checking, property checking, logic synthesis, and false paths. In this paper we describe a new approach for the realization of a BDD package. To perform manipulations of Boolean functions, the proposed approach does not depend on the recursive synthesis operation of the IF-Then-Else (ITE). Instead of using the ITE operation, the basic synthesis algorithm is done using Boolean NOR operation.

Keywords: Binary Decision Diagram (BDD), ITE Operation, Boolean Function, NOR operation.

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Authors: Eduardo Sant'Ana da Silva, Andre Luiz Pires Guedes, Eduardo Todt

Abstract:

Independent spanning trees (ISTs) provide a number of advantages in data broadcasting. One can cite the use in fault tolerance network protocols for distributed computing and bandwidth. However, the problem of constructing multiple ISTs is considered hard for arbitrary graphs. In this paper we present an efficient algorithm to construct ISTs on hypercubes that requires minimum resources to be performed.

Keywords: Hypercube, Independent Spanning Trees, Networks On Chip, Systems On Chip.

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Authors: K. Bashirnezhad, M. Moghiman, M. Javadi Amoli, F. Tofighi, S. Zabetnia

Abstract:

Results are presented from a combined experimental and modeling study undertaken to understand the effect of fuel spray angle on soot production in turbulent liquid spray flames. The experimental work was conducted in a cylindrical laboratory furnace at fuel spray cone angle of 30º, 45º and 60º. Soot concentrations inside the combustor are measured by filter paper technique. The soot concentration is modeled by using the soot particle number density and the mass density based acetylene concentrations. Soot oxidation occurred by both hydroxide radicals and oxygen molecules. The comparison of calculated results against experimental measurements shows good agreement. Both the numerical and experimental results show that the peak value of soot and its location in the furnace depend on fuel spray cone angle. An increase in spray angle enhances the evaporating rate and peak temperature near the nozzle. Although peak soot concentration increase with enhance of fuel spray angle but soot emission from the furnace decreases.

Keywords: Soot, spray angle, turbulent flames, liquid fuel.

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Authors: Miklos Palfia

Abstract:

An iterative definition of any n variable mean function is given in this article, which iteratively uses the two-variable form of the corresponding two-variable mean function. This extension method omits recursivity which is an important improvement compared with certain recursive formulas given before by Ando-Li-Mathias, Petz- Temesi. Furthermore it is conjectured here that this iterative algorithm coincides with the solution of the Riemann centroid minimization problem. Certain simulations are given here to compare the convergence rate of the different algorithms given in the literature. These algorithms will be the gradient and the Newton mehod for the Riemann centroid computation.

Keywords: Means, matrix means, operator means, geometric mean, Riemannian center of mass.

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Authors: Aki Happonen, Adrian Burian, Erwin Hemming

Abstract:

Fixed-point simulation results are used for the performance measure of inverting matrices using a reconfigurable processing element. Matrices are inverted using the Cholesky decomposition algorithm. The reconfigurable processing element is capable of all required mathematical operations. The fixed-point word length analysis is based on simulations of different condition numbers and different matrix sizes.

Keywords: Cholesky Decomposition, Fixed-point, Matrixinversion, Reconfigurable processing.

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Authors: Miloje S. Radenkovic, Tamal Bose

Abstract:

This paper presents the convergence analysis of a prediction based blind equalizer for IIR channels. Predictor parameters are estimated by using the recursive least squares algorithm. It is shown that the prediction error converges almost surely (a.s.) toward a scalar multiple of the unknown input symbol sequence. It is also proved that the convergence rate of the parameter estimation error is of the same order as that in the iterated logarithm law.

Keywords: Adaptive blind equalizer, Recursive leastsquares, Adaptive Filtering, Convergence analysis.

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Authors: S. S. Mishra

Abstract:

In this paper, an attempt is made to compute the total optimal cost of interdependent queuing system with controllable arrival rates as an important performance measure of the system. An example of application has also been presented to exhibit the use of the model. Finally, numerical demonstration based on a computing algorithm and variational effects of the model with the help of the graph have also been presented.

Keywords: Computing, Controllable arrival rate, Optimum performance measure.

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Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

Abstract:

The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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Authors: K. Firsanov, S. Gritsutenko, R. Dinis

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By employing BS (Base Station) cooperation we can increase substantially the spectral efficiency and capacity of cellular systems. The signals received at each BS are sent to a central unit that performs the separation of the different MT (Mobile Terminal) using the same physical channel. However, we need accurate sampling and quantization of those signals so as to reduce the backhaul communication requirements. In this paper we consider the optimization of the quantizers for BS cooperation systems. Four different quantizer types are analyzed and optimized to allow better SQNR (Signal-to-Quantization Noise Ratio) and BER (Bit Error Rate) performance.

Keywords: Base Stations cooperation scheme, Bit Error Rate (BER), Quantizer, Signal to Quantization Noise Ratio (SQNR), SCFDE.

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: Canny pruning, hand recognition, machine learning, skin tracking.

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Authors: N. Belkhir, A. Chorfa, D. Bouzid

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In this work, grinding or microcutting tools in the form of pellets were manufactured using a bounded alumina abrasive grains. The bound used is a vitreous material containing quartz feldspars, kaolinite and a quantity of hematite. The pellets were used in glass grinding process to replace the free abrasive grains lapping process. The study of the elaborated pellets were done to define their effectiveness in the grinding process and to optimize the influence of the pellets elaboration parameters. The obtained results show the existence of an optimal combination of the pellets elaboration parameters for each glass grinding phase (coarse to fine grinding). The final roughness (rms) reached by the elaborated pellets on a BK7 glass surface was about 0.392 μm.

Keywords: Abrasive grain, glass, grinding, pellet.

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Authors: Belkacem Brahmi, Mohand Ouamer Bibi

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In this paper, we present a new method for solving quadratic programming problems, not strictly convex. Constraints of the problem are linear equalities and inequalities, with bounded variables. The suggested method combines the active-set strategies and support methods. The algorithm of the method and numerical experiments are presented, while comparing our approach with the active set method on randomly generated problems.

Keywords: Convex quadratic programming, dual support methods, active set methods.

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Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: Energy efficiency, maximum entropy, reactive systems.

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Authors: Roland Lang, Dietmar Bruckner, Rosemarie Velik, Tobias Deutsch

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Modern building automation needs to deal with very different types of demands, depending on the use of a building and the persons acting in it. To meet the requirements of situation awareness in modern building automation, scenario recognition becomes more and more important in order to detect sequences of events and to react to them properly. We present two concepts of scenario recognition and their implementation, one based on predefined templates and the other applying an unsupervised learning algorithm using statistical methods. Implemented applications will be described and their advantages and disadvantages will be outlined.

Keywords: Building automation, ubiquitous computing, scenariorecognition, surveillance system.

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Authors: A. Thabet, M. Repetto

Abstract:

Dielectric materials play an important role in broad applications, such as electrical and electromagnetic applications. This research studied the prediction of effective permeability of composite and nanocomposite dielectric materials based on theoretical analysis to specify the effects of embedded magnetic inclusions in enhancing magnetic properties of dielectrics. Effective permeability of Plastics and Glass nanodielectrics have been predicted with adding various types and percentages of magnetic nano-particles (Fe, Ni-Cu, Ni-Fe, MgZn_Ferrite, NiZn_Ferrite) for formulating new nanodielectric magnetic industrial materials. Soft nanoparticles powders that have been used in new nanodielectrics often possess the structure of a particle size in the range of micrometer- to nano-sized grains and magnetic isotropy, e.g., a random distribution of magnetic easy axes of the nanograins. It has been succeeded for enhancing characteristics of new nanodielectric magnetic industrial materials. The results have shown a significant effect of inclusions distribution on the effective permeability of nanodielectric magnetic composites, and so, explained the effect of magnetic inclusions types and their concentration on the effective permeability of nanodielectric magnetic materials.

Keywords: Nanoparticles, Nanodielectrics, Nanocomposites, Effective Permeability, Magnetic Properties.

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as metaheuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: Hyper-heuristics, evolutionary algorithms, production scheduling.

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Authors: Sotiris B. Kotsiantis

Abstract:

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Keywords: Regressors, statistical learning.

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Authors: H. Izadbakhsh, M.Hour Ali, A. Amirkhani, A. Montazeri, M. Saberi

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The after–sales activities are nowadays acknowledged as a relevant source of revenue, profit and competitive advantage in most manufacturing industries. Top and middle management, therefore, should focus on the definition of a structured business performance measurement system for the after-sales business. The paper aims at filling this gap, and presents an integrated methodology for the after-sales network performance measurement, and provides an empirical application to automotive case companies and their official service network. This is the first study that presents an integrated multivariate approach for total assessment and improvement of after-sale services.

Keywords: Data Envelopment Analysis (DEA), Principal Component Analysis (PCA), Automotive companies, After-sale services.

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Authors: G. M. Ozkan, H. Akilli

Abstract:

The aim of present study is to control the unsteady flow structure downstream of a circular cylinder by use of attached permeable plates. Particle image velocimetry (PIV) technique and dye visualization experiments were performed in deep water and the flow characteristics were evaluated by means of time-averaged streamlines, Reynolds Shear Stress and Turbulent Kinetic Energy concentrations. The permeable plate was made of a chrome-nickel screen having a porosity value of β=0.6 and it was attached on the cylinder surface along its midspan. Five different angles were given to the plate (θ=0^o, 15^o, 30^o, 45^o, 60^o) with respect to the centerline of the cylinder in order to examine its effect on the flow control. It was shown that the permeable plate is effective on elongating the vortex formation length and reducing the fluctuations in the wake region. Compared to the plain cylinder, the reductions in the values of maximum Reynolds shear stress and Turbulent Kinetic Energy were evaluated as 72.5% and 66%, respectively for the plate angles of θ=45^oand 60^o which were also found to be suggested for applications concerning the vortex shedding and consequent Vortex-Induced Vibrations.

Keywords: Bluff body, flow control, permeable plate, PIV, VIV, vortex shedding.

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Authors: Khalil el Hindi

Abstract:

This paper presents a simple and effective method for approximate indexing of instances for instance based learning. The method uses an interval tree to determine a good starting search point for the nearest neighbor. The search stops when an early stopping criterion is met. The method proved to be very effective especially when only the first nearest neighbor is required.

Keywords: Instance based learning, interval trees, the knn algorithm, machine learning.

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Authors: Vinod Mishra, Dimple Rani

Abstract:

In this paper, numerical approximate Laplace transform inversion algorithm based on Chebyshev polynomial of second kind is developed using odd cosine series. The technique has been tested for three different functions to work efficiently. The illustrations show that the new developed numerical inverse Laplace transform is very much close to the classical analytic inverse Laplace transform.

Keywords: Chebyshev polynomial, Numerical inverse Laplace transform, Odd cosine series.

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Authors: Chokri Baccouch, Chayma Bahhar, Hedi Sakli, Nizar Sakli

Abstract:

In this article, we present the combination of an antenna patch structure with a photovoltaic cell in one device for telecommunication applications in isolated environments. The radiating patch element of a patch antenna was replaced by a solar cell. DC current generation is the original feature of the solar cell, but now it was additionally able to receive and transmit electromagnetic waves. A mathematical model which serves in the minimization of power losses of the cell and therefore the improvement in conversion performance was studied. Simulation results of this antenna show a resonance at a frequency of 16.55 GHz in Ku-band with a gain of 4.24 dBi.

Keywords: Electric power collected, optical and electrical losses, optimization of the grid of collection, patch antenna, photovoltaic cell.

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Authors: Cristian Păuna

Abstract:

In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: Algorithmic trading, automated investment system, DAX Deutscher Aktienindex.

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