我正在制作一个程序来验证31个国家的牌照，每个国家都有不同的格式，并且从某些值开始，它们也不应该包含任何牌照中的字母I，O或Q，以下是格式：
AGUASCALIENTES --from AAA-0001 to AFZ- 9999
BAJA CALIFORNIA-- from AGA-0001 to CYZ-9999
BAJA CALIFORNIA SUR-- from CZA-0001 to DEZ-9999
CAMPECHE -- from DFA-0001 to DKZ-9999
CHIAPAS -- from DLA-0001 to DSZ-9999
CHIHUAHUA -- from DTA-0001 to ETZ-9999
COAHUILA -- from EUA-0001 to FPZ-9999
COLIMA -- from FRA-0001 to FWZ-9999
DURANGO -- from FXA-0001 to GFZ-9999
STATE OF MEXICO -- from LGA-0001 to PEZ-9999
GUANAJUATO -- from GGA-0001 to GYZ-9999
GUERRERO -- from GZA-0001 to HFZ-9999
HIDALGO -- from HGA-0001 to HRZ-9999
JALISCO -- from HSA-0001 to LFZ-9999
MICHOACÁN -- from PFA-0001 to PUZ-9999
MORELOS -- from PVA-0001 to RDZ-9999
NAYARIT -- from REA-0001 to RJZ-9999
NUEVO LEÓN -- from RKA-0001 to TGZ-999
OAXACA -- from THA-0001 to TMZ-9999
PUEBLA-- from TNA-0001 to UJZ-9999
QUERÉTARO-- from UKA-0001 to UPZ-9999
QUINTANA ROO-- from URA-0001 to UVZ-9999
SAN LUIS POTOSÍ-- from UWA-0001 to VEZ-9999
SINALOA-- from VFA-0001 to VSZ-9999
SONORA-- from VTA-0001 to WKZ-9999
TABASCO-- from WLA-0001 to WWZ-9999
TAMAULIPAS-- from WXA-0001 to XSZ-9999
TLAXCALA-- from XTA-0001 to XXZ-9999
VERACRUZ-- from XYA-0001 to YVZ-9999
YUCATÁN-- from YWA-0001 to ZCZ-9999
ZACATECAS-- fromZDA-0001 to ZHZ-9999
根据格式，坎佩切的车牌会是这样的： DGB-5643
我制作了这些模式
Pattern p1 = Pattern.compile("[a][a-z&&[^ioqghjklmnprstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m1 = p1.matcher(field_val.getText()); // aguascalientes
Pattern p2 = Pattern.compile("[a|b|c][a-z&&[^ioqhjklmnprstuvwx]][a-z][-]\\d\\d\\d\\d");
Matcher m2 = p2.matcher(field_val.getText()); // bajac
Pattern p3 = Pattern.compile("[c|d][a-z&&[^ioqfghjklmnprstuvwxy]][a-z][-]\\d\\d\\d\\d");
Matcher m3 = p3.matcher(field_val.getText()); // bajasur
Pattern p4 = Pattern.compile("[d][a-z&&[^ioqabcdelmnprstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m4 = p4.matcher(field_val.getText()); // campeche
Pattern p5 = Pattern.compile("[d][a-z&&[^ioqabcdefghjktuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m5 = p5.matcher(field_val.getText()); // chiapas
Pattern p6 = Pattern.compile("[d|e][a-z&&[^ioqabcdefghjklmnprsuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m6 = p6.matcher(field_val.getText()); // chihuahua
Pattern p7 = Pattern.compile("[e|f][a-z&&[^ioqabcdefghjklmnvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m7 = p7.matcher(field_val.getText()); // coahuila
Pattern p8 = Pattern.compile("[f][a-z&&[^ioqabcdefghjklmnpxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m8 = p8.matcher(field_val.getText()); // colima
Pattern p9 = Pattern.compile("[f|g][a-z&&[^ioqghjklmnprstuvw]][a-z][-]\\d\\d\\d\\d");
Matcher m9 = p9.matcher(field_val.getText()); // durango
Pattern p10 = Pattern.compile("[l|m|n|p][a-z&&[^ioqf]][a-z][-]\\d\\d\\d\\d");
Matcher m10 = p10.matcher(field_val.getText()); // edomex
Pattern p11 = Pattern.compile("[g][a-z&&[^ioqabcdefz]][a-z][-]\\d\\d\\d\\d");
Matcher m11 = p11.matcher(field_val.getText()); // guanajuato
Pattern p12 = Pattern.compile("[g|h][a-z&&[^ioqghjklmnprstuvwxy]][a-z][-]\\d\\d\\d\\d");
Matcher m12 = p12.matcher(field_val.getText()); // guerrero
Pattern p13 = Pattern.compile("[h][a-z&&[^ioqabcdefstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m13 = p13.matcher(field_val.getText()); // hidalgo
Pattern p14 = Pattern.compile("[h|j|k|l][a-z&&[^ioqabcdetuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m14 = p14.matcher(field_val.getText()); // jalisco
Pattern p15 = Pattern.compile("[p][a-z&&[^ioqabcdevwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m15 = p15.matcher(field_val.getText()); // michoacan
Pattern p16 = Pattern.compile("[p|r][a-z&&[^ioqefghjklmnprstu]][a-z][-]\\d\\d\\d\\d");
Matcher m16 = p16.matcher(field_val.getText()); // morelos
Pattern p17 = Pattern.compile("[r][a-z&&[^ioqabcdklmnprstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m17 = p17.matcher(field_val.getText()); // nayarit
Pattern p18 = Pattern.compile("[r|s|t][a-z&&[^ioqhj]][a-z][-]\\d\\d\\d\\d");
Matcher m18 = p18.matcher(field_val.getText()); // nuevoleon
Pattern p19 = Pattern.compile("[t][a-z&&[^ioqabcdefgnprstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m19 = p19.matcher(field_val.getText()); // oaxaca
Pattern p20 = Pattern.compile("[t|u][a-z&&[^ioqklm]][a-z][-]\\d\\d\\d\\d");
Matcher m20 = p20.matcher(field_val.getText()); // puebla
Pattern p21 = Pattern.compile("[u][a-z&&[^ioqabcdefghjrstuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m21 = p21.matcher(field_val.getText()); // queretaro
Pattern p22 = Pattern.compile("[u][a-z&&[^ioqabcdefghjklmnpwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m22 = p22.matcher(field_val.getText()); // quintanaroo
Pattern p23 = Pattern.compile("[u|v][a-z&&[^ioqfghjklmnprstuv]][a-z][-]\\d\\d\\d\\d");
Matcher m23 = p23.matcher(field_val.getText()); // sanluispotosi
Pattern p24 = Pattern.compile("[v][a-z&&[^ioqabcdetuvwxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m24 = p24.matcher(field_val.getText()); // sinaloa
Pattern p25 = Pattern.compile("[v|w][a-z&&[^ioqlmnprs]][a-z][-]\\d\\d\\d\\d");
Matcher m25 = p25.matcher(field_val.getText()); // sonora
Pattern p26 = Pattern.compile("[w][a-z&&[^ioqabcdefghjkxyz]][a-z][-]\\d\\d\\d\\d");
Matcher m26 = p26.matcher(field_val.getText()); // tabasco
Pattern p27 = Pattern.compile("[w|x][a-z&&[^ioqtuvw]][a-z][-]\\d\\d\\d\\d");
Matcher m27 = p27.matcher(field_val.getText()); // tamaulipas
Pattern p28 = Pattern.compile("[x][a-z&&[^ioqabcdefghjklmnprsyz]][a-z][-]\\d\\d\\d\\d");
Matcher m28 = p28.matcher(field_val.getText()); // tlaxcala
Pattern p29 = Pattern.compile("[x][a-z&&[^ioqwx]][a-z][-]\\d\\d\\d\\d");
Matcher m29 = p29.matcher(field_val.getText()); // veracruz
Pattern p30 = Pattern.compile("[y|z][a-z&&[^ioqdefghjklmnprstuv]][a-z][-]\\d\\d\\d\\d");
Matcher m30 = p30.matcher(field_val.getText()); // yucatan
Pattern p31 = Pattern.compile("[z][a-z&&[^ioqabcjklmnprstuvwxy]][a-z][-]\\d\\d\\d\\d");
Matcher m31 = p31.matcher(field_val.getText()); // zacatecas
我将结果发送到名为textfield
res
这里是匹配者
if (m1.find()) {
res.setText(" Your State is Aguascalientes");
} else if (m2.find()) {
res.setText(" Your State is Baja");
} else if (m3.find()) {
res.setText(" Your State is Baja Sur");
} else if (m4.find()) {
res.setText(" Your State is Campeche");
} else if (m5.find()) {
res.setText(" Your State is Chiapas");
} else if (m6.find()) {
res.setText(" Your State is Chihuahua");
} else if (m7.find()) {
res.setText(" Your State is Coahuila");
} else if (m8.find()) {
res.setText(" Your State is Colima");
} else if (m9.find()) {
res.setText(" Your State is Durango");
} else if (m10.find()) {
res.setText(" Your State is Edomex");
} else if (m11.find()) {
res.setText(" Your State is Guanajuato");
} else if (m12.find()) {
res.setText(" Your State is Guerrero");
} else if (m13.find()) {
res.setText(" Your State is Hidalgo");
} else if (m14.find()) {
res.setText(" Your State is Jalisco");
} else if (m15.find()) {
res.setText(" Your State is Michoacan");
} else if (m16.find()) {
res.setText(" Your State is Morelos");
} else if (m17.find()) {
res.setText(" Your State is Nayarit");
} else if (m18.find()) {
res.setText(" Your State is Nuevo Leon");
} else if (m19.find()) {
res.setText(" Your State is Oaxaca");
} else if (m20.find()) {
res.setText(" Your State is Puebla");
} else if (m21.find()) {
res.setText(" Your State is Queretaro");
} else if (m22.find()) {
res.setText(" Your State is Quintana Roo");
} else if (m23.find()) {
res.setText(" Your State is San Luis Potosi");
} else if (m24.find()) {
res.setText(" Your State is Sinaloa");
} else if (m25.find()) {
res.setText(" Your State is Sonora");
} else if (m26.find()) {
res.setText(" Your State is Tabasco");
} else if (m27.find()) {
res.setText(" Your State is Tamaulipas");
} else if (m28.find()) {
res.setText(" Your State is Tlaxcala");
} else if (m29.find()) {
res.setText(" Your State is Veracruz");
} else if (m30.find()) {
res.setText(" Your State is Yucatan");
} else if (m31.find()) {
res.setText(" Your State is Zacatecas");
}
如果第一个字母重复处于两个或三个状态，我没有得到我想要的状态的正确匹配
例如我输入ABH-6262，结果得到Your State is Baja California，我期待得到Aguascalientes
答案 0 :(得分：1)
我假设您在使用这些模式匹配器之前将所有输入字符串转换为小写字母。 （令人困惑的是，你已经忘记了这一点，因为你在谈论大写的车牌号码，但只匹配小写字母。）
我不明白为什么ABH-6262会给你错误的结果。但是，肯定会产生错误结果的组合。例如，您说Edomex应该是从LGA-0001到PEZ-9999。但是，你的模式
Pattern p10 = Pattern.compile("[l|m|n|p][a-z&&[^ioqf]][a-z][-]\\d\\d\\d\\d");
将接受任何首字母为L，M，N或P的组合，这是好的，但也会接受第二个字母不是F（或I，O，Q）的任何组合。这意味着它将接受属于哈利斯科州的LAA;并且它不接受MFA，它应该是Edomex的一部分。
问题是你要比较三个字母和＃34;单词＆＃34;按字母顺序排列，正则表达式是该工作的错误工具。您可以使用类似
的模式执行此操作(l[g-z&&[^ioq]]|[mn][a-z&&[^ioq]]|p[a-e])[a-z&&[^ioq]]-\d\d\d\d
括号中的部分使用|个字符，表示它可以匹配其中一个备选项。在这种情况下，如果下列之一为真（如果没有字母是I，O或Q），它会匹配车牌的前两个字母：
您必须重写许多匹配器才能执行此类操作。但这会使事情变得复杂得多。事实是，你应该使用字符串比较而不是模式匹配器来完成你想要做的事情。
您只需一种模式即可完成此操作：
Pattern licensePlatePattern = Pattern.compile("([a-z&&[^ioq]]{3})-\\d{4}");
注意事项：第一部分匹配任何不是I，O或Q的三个字母;但是这个模式的一部分在括号中，它创建了一个组，以便我们可以稍后查看这三个字母。请注意，这也使用{3}来表示其前面的三个内容（类似{4}）。另请注意，我自己使用-来匹配短划线，而不是[-];在匹配一个特定字符时，您不需要使用[]。
现在：
Matcher matcher = licensePlatePattern.matcher(field_val.getText());
if (matcher.find()) {
String letters = matcher.group(1);
// This gets the part of the input that matches the first parenthesized
// part of the pattern (in this case, the only parenthesized part)
if (letters.compareTo("aaa") >= 0 && letters.compareTo("afz") <= 0) then {
res.setText(" Your State is Aguascalientes");
} else if (letters.compareTo("aga") >= 0 && letters.compareTo("cyz") <= 0) then {
res.setText(" Your State is Baja");
} else if (letters.compareTo("cza") >= 0 && letters.compareTo("dez") <= 0) then {
res.setText(" Your State is Baja Sur");
等等。这比拥有31种复杂模式更容易理解。更好的方法是将状态信息放在一个数组中，比如
public class StateInfo {
private String name;
private String lowestThreeLetters;
private String highestThreeLetters;
// constructor, getters -- I'll let you figure out how to write these
}
// in some other class:
public static final StateInfo[] stateInfo = new StateInfo[] {
new StateInfo("Aguascalientes", "aaa", "afz"),
new StateInfo("Baja", "aga", "cyz"),
new StateInfo("Baja Sur", "cza", "dez"),
... };
而不是31个if语句，您可以遍历数组：
String letters = matcher.group(1);
for (StateInfo s : stateInfo) {
if (letters.compareTo(s.getLowestThreeLetters()) >= 0 &&
letters.compareTo(s.getHighestThreeLetters()) <= 0) {
res.setText(" Your State is " + s.getName());
break;
}
}
答案 1 :(得分：0)
如果您想同时检查大写和小写，可以使用它
Pattern p1 = Pattern.compile("[a|A][a-f[A-F]][a-z[A-Z]&&[^ioqIOQ]][-][0-9][0-9][0-9][1-9]");
Matcher m1 = p1.matcher(field_val); // aguascalientes
Pattern p2 = Pattern.compile("[a-c[A-C]][g-y[G-Y]&&[^ioqIOQ]][a-z[A-Z]&&[^ioqIOQ]][-][0-9][0-9][0-9][1-9]");
Matcher m2 = p2.matcher(field_val); // bajac
答案 2 :(得分：-1)
这对我有用。但是，没有检查细节。但是你的模式可以稍微提高一点。试试这个模式：
Pattern p1 = Pattern.compile("[a|A][a-f][a-z&&[^ioq]][-][0-9][0-9][0-9][1-9]");
Matcher m1 = p1.matcher(field_val); // aguascalientes
Pattern p2 = Pattern.compile("[a-c][g-y&&^[ioq]][a-z&&[^ioq]][-][0-9][0-9][0-9][1-9]");
Matcher m2 = p2.matcher(field_val);
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