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Aiming at the problem that the dual-frequency ultrasonic extraction of puerarin is difficult to detect effectively and efficiently with the method of manually watching and off-line detection, a method of soft sensor modeling is proposed. In the method, the genetic algorithm and the support vector machine (GA-SVM) are combined to build the soft measurement model of the puerarin extraction. By using...
The ports which are often open on different hosts at different times are extremely important for network security analyses because they supply more attack chances to attackers. These ports can be discovered by sequential port scans. For network defenders, main concern about port scans is not the stealth, but the efficiency, especially on large and complex networks. Based-on partheno-genetic algorithm,...
The on-line optimal control of operation is difficult to achieve with routine optimization methods because of the nonlinear thermal system and the changing frequently conditions in start-up, stop and load change of the large-scale thermal power plant. Based on the research of three typical evolution optimization methods which are evolution strategies, genetic algorithm and evolution programming in...
This paper applied a genetic algorithm (GA) to optimize the parameters of support vector machine (SVM) for daily flow forecasting of Chickasaw creek located in Mobile County. To investigate the impact of variable enabling/disabling of flow, rainfall and evaporation on model prediction accuracy, four model structures with different input vectors were developed and the performance of them was evaluated...
Bayesian Networks is a popular tool for representing uncertainty knowledge in artificial intelligence fields. Learning BNs from data is helpful to understand the casual relation between variables. But Learning BNs is a NP hard problem. This paper presents an immune genetic algorithm for learning Markov equivalence classes, which combining dependency analysis and search-scoring approach together. Experiments...
This paper propose an IPGA based multi-objective compatible control algorithm to control oversaturated adjacent intersections. The concept of feeding delay and non-feeding delay is introduced; A BPNN method is used to set up a MIMO delay model based on the simulated data got from cell transmission model. Then, the control problem is formulated as an conflicted multi-objective control problem, and...
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