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Download ESTECO modeFRONTIER 4.5.4

modeFRONTIER - an environment for solving multiobjective optimization criterion and working with various CAD, CAE, CFD and other software systems. In the environment there is the opportunity to work in an automatic design and optimization of products. Implemented Data processing and analysis using various methods
Main technical characteristics:
Planning of experiment (DOE), the population distribution of the input variables, the estimation accuracy of the forecast
User DOE; Random; Sobol; Full factorial; Cubic-face-centered; Taguchi; Box-Benken; Montecarlo; Reduced Factorial; Latin Square; Latin Hypercube;
D-Optimal; The method of cross-validation (cross validation); Constraint satisfaction problems (constraint satisfaction problem).
Decision-making during the multi-criteria optimization (MCDM):
Hurwitz criterion (Hurwicz criterion);
Linear algorithm;
GA algoriphm;
Minimax, savage mimimax regret criterion;
Algorithms, optimization techniques:
DOE Sequence - direct search parameters;
MOGA II - genetic algorithm for multiobjective optimization;
ARMOGA - genetic algorithm based on MOGA;
NSGA II - non-dominated sorting genetic algorithm for multiobjective optimization;
NASH - algorithm based on the theory of noncooperative games Nash (Nash), for multiobjective optimization;
B-BFGS - gradient algorithm;
SIMPLEX - search for a solution without the use of derivatives by the method of Nelder-Mead;
Levenberg-Marquardt (Levenberg-Marquardt);
Simulated Annealing- hardening modeling algorithm (method of simulated annealing);
1P1-ES - evolutionary strategy;
DES - evolutionary strategy for the optimization criterion with continuous variables;
MMES - evolutionary strategy for multi-criteria optimization with discrete and continuous variables;
FMOGA II - version of MOGA algorithm with improved convergence;
FSIMPLEX - Simplex version with improved convergence and possible solutions of multiobjective problems;
MOSA - version of simulated annealing with the possibility of solving multiobjective problems;
MACK - approximation algorithm for the response surfaces;
NLPQLP - algorithm of sequential quadratic programming (SQP);
NLPQLP-NBI - Normal Boundary Intersection method + NLPQLP (algorithm with the possibility of solving multiobjective nonlinear problems);
Multi-Objective Particle Swarm.
Metamodel (response surface approximation, RSM, approximate mathematical model), methods of construction:
K-Nearest (method Shepard-a);
SVD (singular value decomposition);
Kriging (Kriging), a technique of regression analysis based on the works of Daniel Krige;
Parametric surfaces, polynomial regression;
Gaussian Processes - approach to solving problems of regression analysis based on the works of Beziers (Bayesian);
Artificial neural networks, radial basis neural network (radial basis function),
Means of validation meta - models.
6 Sigma, quality management, Design for Six Sigma (DFSS):
Quality Sigma (six sigma quality);
Failure modes and effects analysis of their (discards analysis);
Ishikawa diagram.
Visual analysis of data, evaluation of the statistical significance of the data:
The probability density function (probability density function);
Investigation of the relationship between variables, scatterDescription, line, bubble chart, the trend line;
The distribution of the data, histogram, "pie', cumilative Description;
Linear correlation analysis, correlation matrix (correlation matrix), matrix dispersion (scatter matrix), matrix effects
(effects matrix);
Determination of the main characteristics of the sample, "box and whisker' (box-whiskers), the quantile Description (Quantile-Quantile Description);
Calculation of the tightness of interaction parameters;
Working with data samples of high dimensionality, Student's t test, analysis of variance (test Bon-Ferroni, ANOVA);
Check sampling (distribution fitting);
Cluster analysis methods:
- Partitive clustering
- Methods of hierarchical cluster analysis (hierarchical clustering) - average-linkage, centroid-linkaga, complete-linkaga, single-linkage,
ward approach,
- K-means algorithm (K-Means Clustering), Forgy approach, Kaufman approach, Macqueen approach, random
- Algorithm for self-organizing maps (SOMs),
- dendrogram
Experience of use in various fields:
- Optimization of the form inlets
- Optimization of the cooling system
- Optimization of the flow of air in the engine compartment
- Reducing vibrations
- Aerospace
- Optimizing the shape of a centrifugal compressor
- Optimizing the shape of an axial turbine and axial compressor
- General Engineering
- Optimization of injection molding process
- Optimization of the casting of metals
- Optimization of the technology of hot stamping
- Marine Construction
- Optimizing the ship hull, reducing drag
- Optimal design steering
- Financial markets
- The problem of optimizing the investment portfolio of shares
- Decision-making in the financial market
In modeFRONTIER implemented to work with a number of software systems:
AMESim; AVL Boost; AVL Hydsim; Flowmaster; GT-Power; KULI; Wave Aspen PLUS; CHEMKIN; eta / VPG; LS-DYNA; MADYMO; RADIOSS; Mathematica;
Matlab; DEP; MS Excel; MySQL; OpenOffice; Winbatch; ADAMS; Carsim; Dymola; RecurDyn; SIMPACK; Virtual.Lab; CADFix; CATIA; SolidWorks; I-DEAS;
UnigraphicsNX; Maxsurf; ProEngineer; JMAG; AVL-Fame; ICEMCFD; GID; Gridgen; MSC Patran; Paramesh; Sculptor; AdvantEdge; Cadmould; Magma COMSOL Multiphysiscs (FEMLAB); Simulink; ANSYS CFX; ANSYS TASCflow; FIDAP; FLUENT; GAMBIT; AVL-Fire; Star-CD; Star-CCM +; Star-Design; ABAQUS
ANSYS; ANSYS Workbench; AVL-Excite; eta / VPG; MSC MARC; MSC NASTRAN; PERMAS; SAMCEF; STRAUS7; SYSNOISE Fieldview; Friendship; Icare;
NAPA4; Nu-SHALLO; RAPID; REVA; Shipflow Condor; GridEngine; IBM LoadLeveler; LSF; NQS
Extras. Information: Distributions and universal scrap for Windows (x86 + x64), Linux (x86 + 64), and UNIX. Just added to the sample files and Tutorials on modeFRONTIER.
Year / Release Date: 2014
Version: 4.5.4
Developer: ESTECO s.r.l
Developer website:
Bit depth: 32bit + 64bit
Compatibility with Vista: complete
Compatible with Windows 7: complete
Language: Multilingual
Medicine: Present
OS: Win/Mac/Linux/UNIX
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