摘要：【中文】本发明公开了一种锅炉优化燃烧控制方法，包括锅炉汽包水位控制回路，锅炉汽包水位控制回路的控制包括以下步骤：S1：分别对锅炉汽包水位、给水流量、主蒸汽流量的偏差值进行采集；S2：计算锅炉的主给水调节门、副给水调节门控制调节量：对主给水调节门、副给水调节门控制调节量按照以下计算公式计算得出：其中，WQ为调节器输出信号；Ws为调节器的偏差信号；Kp是比例系数；Ti是积分时间；Td是微分时间，通过消除人为误差和硬件误差，依托优化后的软件，将锅炉各控制回路投入自动优化运行，该系统能保证企业安全运行生产，节约能源，从而给企业带来可观的经济利益。 【EN】The invention discloses a boiler optimized combustion control method, which comprises a boiler drum water level control loop, wherein the control of the boiler drum water level control loop comprises the following steps: s1: collecting deviation values of a boiler drum water level, a feed water flow and a main steam flow respectively; s2: calculating the control regulating quantity of a main water supply regulating gate and an auxiliary water supply regulating gate of the boiler: the control regulating quantity of the main water supply regulating valve and the auxiliary water supply regulating valve is calculated according to the following calculation formula:wherein WQ is the regulator output signal; ws is the deviation signal of the regulator; kp is a proportionality coefficient; ti is the integration time; td is differential time, each control loop of the boiler is put into automatic optimization operation by eliminating human errors and hardware errors and relying on optimized software, and the system can ensure safe operation and production of enterprises and save energy, thereby bringing considerable economic benefits to the enterprises.

摘要：【中文】本发明提出一种基于模式拓展的通用特殊词识别方法及系统，提出了一种基于基础词的音形编码，常用汉字音节，常用汉字结构以及特殊字符映射节点来构建前缀树，通过比较字符编码相似度进行模糊匹配，完成新词提取的方法及系统。本发明可以应用于大量文本中特定词的发现提取，某些任务的数据集的提取生成，给定文本数据集的预处理等场景中，比如短信、微博等数据集的筛选以及纠正等文本预处理过程。本发明为下一步的文本分类任务提供了数据来源和基本标注，也对文本数据中新词的发现和纠正提供了帮助。 【EN】The invention provides a general special word recognition method and system based on mode expansion, and provides a method and system for constructing a prefix tree based on sound-shape coding of basic words, syllables of common Chinese characters, structures of the common Chinese characters and special character mapping nodes, and performing fuzzy matching by comparing character coding similarity to finish new word extraction. The method can be applied to the scenes of finding and extracting specific words in a large number of texts, extracting and generating data sets of certain tasks, preprocessing given text data sets and the like, such as text preprocessing processes of screening and correcting data sets of short messages, microblogs and the like. The invention provides a data source and a basic label for the next text classification task and also provides help for finding and correcting new words in the text data.

摘要：【中文】本发明提出了一种基于多模型集成的短文本分类方法，包括：选取多个对短文本进行分类的分类模型；对训练样本进行采样，生成与该分类模型一一对应的训练集；通过对应的训练集对该分类模型进行训练，以获得对应的最终模型；通过所有该最终模型对目标文本进行分类，获取多个分类结果向量；集成所有该分类结果向量以得到最终结果向量，以该最终结果向量中具有最大值的元素所代表的类别，作为该目标文本的类别。 【EN】The invention provides a short text classification method based on multi-model integration, which comprises the following steps: selecting a plurality of classification models for classifying the short texts; sampling the training samples to generate a training set corresponding to the classification model one by one; training the classification model through a corresponding training set to obtain a corresponding final model; classifying the target text through all the final models to obtain a plurality of classification result vectors; and integrating all the classification result vectors to obtain a final result vector, and taking the class represented by the element with the maximum value in the final result vector as the class of the target text.