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COSTA RICA的国旗
tres rios, costa rica
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Orlando R.

@gogoulor

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Mechanical Engineer. Magister Scientiarum in System Engineering.

Experience in: Mechanical design, cost estimation, hydrographic survey, Photoshop, 3D modeling, blog edition, process planing, project planning, geographic information systems, finite element method. please see [login to view URL]

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的国旗 Brajesh C.
@bchandra1955
7 年前

经验

Subaquatic development manager

SEA Corp
1月 2011 - 现在
Hydrographic studies as a sonar operator of Kongsberg Mesotech MS 1000 in hight resolution imaging and bathymetry by echo-sound, mosaicing, subaquatic surface generation since point cloud. Selection and equipment design, load and stress simulation simulación using Algor, Inventor and Solidworks, 3D design and drafting, cost estimator, personnel, equipment and bill of materials.

教育

Magister Scientiarum in system engineering

Universidad Simón Bolívar, Venezuela 2002 - 2008
(6 年)

Mechanical Engineer

Universidad Central de Venezuela, Venezuela 1992 - 1999
(7 年)

资质

Wreck diver

ANDI Latinoamerica
2012
Penetration of wrecks using the right techniques

Complete Safe Air User

ANDI Latinoamerica
2012
diving until 40m depth using properly, adequate equipment and nitrox (changing the mix of nitrogen and oxigen)

Open water diver

Xprodiver
2011
diving until 30m depth using properly and the adequate equipment

出版物

Diseño de Controladores PID Multi-Objetivo mediante Algoritmos Genéticos incluyendo el Cálculo de los Límites de la Región de Controladores Estabilizantes

AVAC
Una de las principales críticas que se formulan con respecto a la aplicación de algoritmos genéticos para resolver problemas de optimización no-convexa, se basa en que en muchos casos los límites del espacio de búsqueda deben ser definidos por el usuario de manera arbitraria. En este trabajo se presenta un método que permite solucionar en parte este problema, al menos en el caso del diseño de controladores PID multi-objetivo. Durante la primera etapa s

Algorithm to Describe the Ideal Spur Gear Profile

IAENG; ISBN: 978-988-98671-9-52 de julio de 2008
In this paper an algorithm to describe the ideal spur gear profile is proposed. The involute of the base circle is used to draw the tooth. Three parameters are the required algorithm inputs: the modulus, the number of teeth and the pressure angle. The algorithm is based upon the equations of the circular head and root thickness. A pseudocode is given which can be translated into any machine language. Two codes are also proposed in order to test the algorithm: A Visual Basic code (which can run as a macro i

A Multi-Objetive-Approach to Approximate the Stabilizing Region for Linear Control Systems

INSTICC; ISBN: 978-989-8111-99-92 de junio de 2009
Stability is a crucial issue to consider for control system design. In this paper a new multi-objective approach to approximate the stabilizing region for linear control systems is proposed. The design method comprises two stages. In the first stage, a bi-objective sub-problem is solved: the algorithm aims to calculate the vertices that maximize both the volume of the decision space and the percent of stable individuals generated within the decision space. In the second stage, the information gathered durin

Multiobjetive Ga-Fuzzy Logig Controller

INSTICC; ISBN: 978-989-8111-99-92 de junio de 2009
A Takagi-Sugeno (T-S) Fuzzy Logic Controller (FLC) is tuned using the algorithm NSGA-II. The proposed method eliminates laborious design steps such as tuning of membership functions and conclusion table parameters. An object approach representation is used to build an adequate FLC representation. Object is an individual abstraction in order to improve crossover a mutation operators. The Genetic Algorithm optimization is carry out over signal response performance parameters, in this work: settling time, rise

Using Genetic Algorithms to Desing a Fuzzy Logic Controller for a PH Reator: An Object Approach

ACTA Press; Editor: C.A. Rabbath; CD ISBN: 978-0-88986-746-829 de mayo de 2008
This paper presents a Fuzzy Logic Controller (FLC) designed through Genetic Algorithms (GA). The genetic representation follows an "object approach", with attributes and methods for each controller element: membership functions, conclusions tables and fitness values. Special mutation and crossover operators are also discussed. Results show that the proposed method is able to find good controllers for the target plant: a pH reactor operating near to the neutral point.

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