نتایج جستجو برای: process parameter optimization
تعداد نتایج: 1744699 فیلتر نتایج به سال:
abstract: in this paper, an exergy analysis approach is proposed for optimal design of distillation column by using simulated annealing algorithm. first, the simulation of a distillation column was performed by using the shortcut results and irreversibility in each tray was obtained. the area beneath the exergy loss profile was used as irreversibility index in the whole column. then, first opti...
a real-time optimization (rto) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. furthermore, the objective function is penalized by a fuzzified form of the key process constraints. to enable using conventional optimization techniques, the resulting fuzzy optimization problem is then re...
A new technique to find the optimization parameter in TSVD regularization method is based on a curve which is drawn against the residual norm [5]. Since the TSVD regularization is a method with discrete regularization parameter, then the above-mentioned curve is also discrete. In this paper we present a mathematical analysis of this curve, showing that the curve has L-shaped path very similar t...
Abstract—Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far...
Bayesian optimization (BO) is a sample-efficient method for global optimization of expensive, noisy, black-box functions using probabilistic methods. The performance of a BO method depends on its selection strategy through the acquisition function. Expected improvement (EI) is one of the most widely used acquisition functions for BO that finds the expectation of the improvement function over th...
The parameter values used for the Growing Neural Gas (GNG) algorithm are generally determined empirically. This requires long calculation times and may lead to values which are not optimized for the data set they are being used with. The present work proposes the use of Evolutionary Algorithms to optimize these parameter values. During the optimization process, GNG networks are created with the...
As a modified version of GGH map, Gu map-1 was successful in constructing multi-party key exchange (MPKE). In this short paper we present a result about the parameter setting of Gu map-1, therefore we can reduce a key parameter τ from original O(n) down to O(λn) (in theoretically secure case, where λ is the security parameter), and even down to O(2n) (in computationally secure case). Such optim...
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