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Stochastic optimization is playing an increasingly important in machine learning in the big data era. In this paper, we use forward-backward splitting for the stochastic optimization problems, where the objective is the sum of two functions: one is the expected risk function, another is a regularized term. At each iteration of this method, we just use a single sample to adjust the variables. We prove...
Analytical theory and simulation-based analysis for optimizing sensitivity of RF energy harvester are discussed. A target harvester is a widely-used MOSFET Dickson charge-pump harvester from a small-signal RF power with a voltage booster at the front end. Charging time is also analyzed. Derived expressions show good match with simulation results. The results provide an insight for design optimization...
In this paper, aiming at the water-consuming of the circulating water system in the petrochemical enterprises, the stage-wise super structure model of the heat exchanger network is established. And the model can be solved by using the MINLP programming method. Considering the characteristics of no-shunt and shunt, the simultaneous optimization of heat exchanger networks is implemented, which is based...
There are vast amount researches in Evolutionary Algorithms (EA). We need an overview of the current state of EA research every few years. This paper reviews some of the interesting researches at the current state in both theory and application of EA. Works in EA performance improvements are introduced in the sense of balancing between convergence speed and diversity in the population. The combination...
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