可恶的编码,可恶的MYSQL

本文详细介绍了MySQL中因字符集不一致导致的错误,并分享了解决方案,包括统一my.ini配置、数据库表及字段字符集的过程。
    这两天总是给我出来[Illegal mix of collations ( gb2312_chinese_ci,IMPLICIT) and ( gbk_chinese_ci,COERCIBLE) for operation '='] 的错误,搞了很久,重新安装Mysql,更改Mysql的默认启动参数,更改my.in文件等等,更该每个表的默认字符集,折腾了一溜够,终于领略了Mysql的魅力,不过也终于明白了一些问题。
    它出现这个错误的主要原因就是字符集的事情,两个不同的字符集比较的时候,不能比较,因为它比较的时候,都是把字符(symbols )转换成了编码(encodings),然后才能比较大小和相等。不同的字符(symbols )在不同的字符集中的编码(encodings)是不同的,所以不能简单地比较,但是这个破东西是不是弄得太复杂了:(
   
   PS:我修改的地方,my.ini里面把所有的都改成了gb2312,更改数据库和表,字段等,都改成了gb2312,还有连接JDBC处(jdbc:mysql://localhost/bugreport?useUnicode=true&characterEncoding=gb2312)
A character set is a set of symbols and encodings. A collation is a set of rules for comparing characters in a character set. Let's make the distinction clear with an example of an imaginary character set.
Suppose that we have an alphabet with four letters: `A', `B', `a', `b'. We give each letter a number: `A' = 0, `B' = 1, `a' = 2, `b' = 3. The letter `A' is a symbol, the number 0 is the encoding for `A', and the combination of all four letters and their encodings is a character set.
Now, suppose that we want to compare two string values, `A' and `B'. The simplest way to do this is to look at the encodings: 0 for `A' and 1 for `B'. Because 0 is less than 1, we say `A' is less than `B'. Now, what we've just done is apply a collation to our character set. The collation is a set of rules (only one rule in this case): ``compare the encodings.'' We call this simplest of all possible collations a binary collation.
But what if we want to say that the lowercase and uppercase letters are equivalent? Then we would have at least two rules: (1) treat the lowercase letters `a' and `b' as equivalent to `A' and `B'; (2) then compare the encodings. We call this a case-insensitive collation. It's a little more complex than a binary collation.
In real life, most character sets have many characters: not just `A' and `B' but whole alphabets, sometimes multiple alphabets or eastern writing systems with thousands of characters, along with many special symbols and punctuation marks. Also in real life, most collations have many rules: not just case insensitivity but also accent insensitivity (an ``accent'' is a mark attached to a character as in German `Ö') and multiple-character mappings (such as the rule that `Ö' = `OE' in one of the two German collations).
 
内容概要:本文提出了一种基于融合鱼鹰算法和柯西变异的改进麻雀优化算法(OCSSA),用于优化变分模态分解(VMD)的参数,进而结合卷积神经网络(CNN)与双向长短期记忆网络(BiLSTM)构建OCSSA-VMD-CNN-BILSTM模型,实现对轴承故障的高【轴承故障诊断】基于融合鱼鹰和柯西变异的麻雀优化算法OCSSA-VMD-CNN-BILSTM轴承诊断研究【西储大学数据】(Matlab代码实现)精度诊断。研究采用西储大学公开的轴承故障数据集进行实验验证,通过优化VMD的模态数和惩罚因子,有效提升了信号分解的准确性与稳定性,随后利用CNN提取故障特征,BiLSTM捕捉时间序列的深层依赖关系,最终实现故障类型的智能识别。该方法在提升故障诊断精度与鲁棒性方面表现出优越性能。; 适合人群:具备一定信号处理、机器学习基础,从事机械故障诊断、智能运维、工业大数据分析等相关领域的研究生、科研人员及工程技术人员。; 使用场景及目标:①解决传统VMD参数依赖人工经验选取的问题,实现参数自适应优化;②提升复杂工况下滚动轴承早期故障的识别准确率;③为智能制造与预测性维护提供可靠的技术支持。; 阅读建议:建议读者结合Matlab代码实现过程,深入理解OCSSA优化机制、VMD信号分解流程以及CNN-BiLSTM网络架构的设计逻辑,重点关注参数优化与故障分类的联动关系,并可通过更换数据集进一步验证模型泛化能力。
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