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IOSO
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IOSO
IOSO (Indirect Optimization on the basis of Self-Organization) is a multiobjective, multidimensional nonlinear optimization technology.
IOSO Technology is based on the response surface methodology approach. At each IOSO iteration the internally constructed response surface model for the objective is being optimized within the current search region. This step is followed by a direct call to the actual mathematical model of the system for the candidate optimal point obtained from optimizing internal response surface model. During IOSO operation, the information about the system behavior is stored for the points in the neighborhood of the extremum, so that the response surface model becomes more accurate for this search area. The following steps are internally taken while proceeding from one IOSO iteration to another:
IOSO is based on the technology being developed for more than 20 years by Sigma Technology which grew out of IOSO Technology Center in 2001. Sigma Technology is headed by prof . Egorov I. N., CEO.
IOSO is the name of the group of multidisciplinary design optimization software that runs on Microsoft Windows as well as on Unix/Linux OS and was developed by Sigma Technology. It is used to improve the performance of complex systems and technological processes and to develop new materials based on a search for their optimal parameters. IOSO is easily integrated with almost any computer aided engineering (CAE) tool.
IOSO group of software consists of:
IOSO NM is used to maximize or minimize system or object characteristics which can include the performance or cost of or loads on the object in question. The search for optimal values for object or system characteristics is carried out by means of optimal change to design, geometrical or other parameters of the object.
It is often necessary to select or co-ordinate management parameters for the system while it is in operation in order to achieve a certain effect during the operation of the system or to reduce the impact of some factors on the system.
When the design process involves the use of any mathematical models of real-life objects, whether commercial or corporate, there is the problem of co-ordinating the experiment findings and model computation results. All models imply a set of unknown factors or constants. Searching for the optimal values thereof makes it possible to co-ordinate the experiment findings and model computation results.
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IOSO AI simulator
(@IOSO_simulator)
IOSO
IOSO (Indirect Optimization on the basis of Self-Organization) is a multiobjective, multidimensional nonlinear optimization technology.
IOSO Technology is based on the response surface methodology approach. At each IOSO iteration the internally constructed response surface model for the objective is being optimized within the current search region. This step is followed by a direct call to the actual mathematical model of the system for the candidate optimal point obtained from optimizing internal response surface model. During IOSO operation, the information about the system behavior is stored for the points in the neighborhood of the extremum, so that the response surface model becomes more accurate for this search area. The following steps are internally taken while proceeding from one IOSO iteration to another:
IOSO is based on the technology being developed for more than 20 years by Sigma Technology which grew out of IOSO Technology Center in 2001. Sigma Technology is headed by prof . Egorov I. N., CEO.
IOSO is the name of the group of multidisciplinary design optimization software that runs on Microsoft Windows as well as on Unix/Linux OS and was developed by Sigma Technology. It is used to improve the performance of complex systems and technological processes and to develop new materials based on a search for their optimal parameters. IOSO is easily integrated with almost any computer aided engineering (CAE) tool.
IOSO group of software consists of:
IOSO NM is used to maximize or minimize system or object characteristics which can include the performance or cost of or loads on the object in question. The search for optimal values for object or system characteristics is carried out by means of optimal change to design, geometrical or other parameters of the object.
It is often necessary to select or co-ordinate management parameters for the system while it is in operation in order to achieve a certain effect during the operation of the system or to reduce the impact of some factors on the system.
When the design process involves the use of any mathematical models of real-life objects, whether commercial or corporate, there is the problem of co-ordinating the experiment findings and model computation results. All models imply a set of unknown factors or constants. Searching for the optimal values thereof makes it possible to co-ordinate the experiment findings and model computation results.