According to the characteristics of injection products, a K-Nearest Neighbors (K-NN) case retrieval strategy was proposed based on rough set and simulated annealing algorithm.
针对注塑产品特点，提出了基于粗糙集和模拟退火算法的事例最邻近检索策略。
Annealing also relieves internal stresses previously set up in the metal.
退火也释放了先前在金属中的内应力。
Annealing voltage is freely adjustable and Annealing time can be set from 0 to 10 minutes.
退火电压可进行无级调节，退火时间从0到10分钟任意可调。
Therefore, the mathematic model for optimization disinfection was set up, and the hybrid genetic-simulated annealing algorithm was used for solution.
为此，建立了优化消毒数学模型，并采用遗传—模拟退火混合算法对其进行求解。
By making use of simulated annealing algorithm with memory, and determining a set of effective cooling schedule, the thesis solves this complex and special knapsack problem successfully.
本文应用带记忆功能的模拟退火演算法，结合理论分析和经验法则，通过大量试验确定了一组有效的冷却进度表参数，成功地解决了这个复杂而特殊的背包问题。
By making use of simulated annealing algorithm with memory, and determining a set of effective cooling schedule, the thesis solves this complex and special knapsack problem successfully.
本文应用带记忆功能的模拟退火演算法，结合理论分析和经验法则，通过大量试验确定了一组有效的冷却进度表参数，成功地解决了这个复杂而特殊的背包问题。
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