. "1808639"^^ . . . "\u0424\u0443\u043D\u043A\u0446\u0456\u044F \u043D\u0430\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0456 \u043D\u0435\u0447\u0456\u0442\u043A\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438 \u2014 \u0443\u0437\u0430\u0433\u0430\u043B\u044C\u043D\u0435\u043D\u043D\u044F \u0445\u0430\u0440\u0430\u043A\u0442\u0435\u0440\u0438\u0441\u0442\u0438\u0447\u043D\u043E\u0457 (\u0456\u043D\u0434\u0438\u043A\u0430\u0442\u043E\u0440\u043D\u043E\u0457) \u0444\u0443\u043D\u043A\u0446\u0456\u0457 \u043A\u043B\u0430\u0441\u0438\u0447\u043D\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438. \u0412 \u043D\u0435\u0447\u0456\u0442\u043A\u0456\u0439 \u043B\u043E\u0433\u0456\u0446\u0456 \u0432\u043E\u043D\u0430 \u044F\u0432\u043B\u044F\u0454 \u0441\u043E\u0431\u043E\u044E \u043A\u043E\u0436\u043D\u043E\u0433\u043E \u0447\u043B\u0435\u043D\u0430 \u043F\u0440\u043E\u0441\u0442\u043E\u0440\u0443 \u043C\u0456\u0440\u043A\u0443\u0432\u0430\u043D\u044C \u0434\u043E \u0434\u0430\u043D\u043E\u0457 \u043D\u0435\u0447\u0456\u0442\u043A\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438."@uk . . . "\u96B8\u5C6C\u51FD\u6578"@zh . . . "\u96B8\u5C6C\u51FD\u6578\uFF08membership function\uFF09\u4E5F\u7A31\u70BA\u6B78\u5C6C\u51FD\u6578\u6216\u6A21\u7CCA\u5143\u51FD\u6578\uFF0C\u662F\u6A21\u7CCA\u96C6\u5408\u4E2D\u6703\u7528\u5230\u7684\u51FD\u6578\uFF0C\u662F\u4E00\u822C\u96C6\u5408\u4E2D\u6307\u793A\u51FD\u6578\u7684\u4E00\u822C\u5316\u3002\u6307\u793A\u51FD\u6578\u53EF\u4EE5\u8AAA\u660E\u4E00\u500B\u96C6\u5408\u4E2D\u7684\u5143\u7D20\u662F\u5426\u5C6C\u65BC\u7279\u5B9A\u5B50\u96C6\u5408\u3002\u4E00\u5143\u7D20\u7684\u6307\u793A\u51FD\u6578\u7684\u503C\u53EF\u80FD\u662F0\u6216\u662F1\uFF0C\u800C\u4E00\u5143\u7D20\u7684\u96B8\u5C6C\u51FD\u6578\u6703\u662F0\u52301\u4E4B\u9593\u7684\u6578\u503C\uFF0C\u8868\u793A\u5143\u7D20\u5C6C\u65BC\u67D0\u6A21\u7CCA\u96C6\u5408\u7684\u300C\u771F\u5BE6\u7A0B\u5EA6\u300D\uFF08degree of truth\uFF09\u3002 \u4F8B\u5982\u8CEA\u6578\u70BA\u4E00\u96C6\u5408\uFF0C\u6574\u65783\u5C6C\u65BC\u8CEA\u6578\uFF0C\u5176\u6307\u793A\u51FD\u6578\u70BA1\uFF0C\u6574\u65784\u4E0D\u5C6C\u65BC\u8CEA\u6578\uFF0C\u5176\u6307\u793A\u51FD\u6578\u70BA0\u3002\u4F46\u91DD\u5C0D\u6A21\u7CCA\u96C6\u5408\uFF0C\u53EF\u80FD\u4E0D\u6703\u6709\u5982\u6B64\u660E\u78BA\u7684\u5B9A\u7FA9\uFF0C\u5047\u8A2D\u80D6\u5B50\u662F\u6A21\u7CCA\u96C6\u5408\uFF0C\u53EF\u80FD\u9AD4\u91CD80\u516C\u65A4\u7684\u4EBA\u5176\u96B8\u5C6C\u51FD\u6578\u70BA0.9\uFF0C\u9AD4\u91CD70\u516C\u65A4\u7684\u4EBA\u5176\u96B8\u5C6C\u51FD\u6578\u70BA0.8\u3002 \u96B8\u5C6C\u51FD\u6578\u6578\u503C\u662F\u57280\u52301\u4E4B\u9593\uFF0C\u770B\u4F3C\u985E\u4F3C\u6A5F\u7387\uFF0C\u4F46\u5169\u8005\u662F\u4E0D\u540C\u7684\u6982\u5FF5\u3002 \u96B8\u5C6C\u51FD\u6578\u6700\u65E9\u662F\u7531\u76E7\u83F2\u7279\u00B7\u6FA4\u5FB7\u57281965\u5E74\u7B2C\u4E00\u7BC7\u6709\u95DC\u6A21\u7CCA\u96C6\u5408\u7684\u8AD6\u6587\u4E2D\u63D0\u53CA\uFF0C\u4ED6\u5728\u6A21\u7CCA\u96C6\u5408\u7684\u8AD6\u6587\u4E2D\uFF0C\u63D0\u51FA\u7528\u503C\u57DF\u57280\u52301\u4E4B\u9593\u7684\u96B8\u5C6C\u51FD\u6578\uFF0C\u91DD\u5C0D\u5B9A\u7FA9\u57DF\u4E2D\u6240\u6709\u7684\u6578\u503C\u5B9A\u7FA9\u3002"@zh . . . . "4060"^^ . "\u0424\u0443\u043D\u043A\u0446\u0438\u044F \u043F\u0440\u0438\u043D\u0430\u0434\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0438"@ru . . . . "\u0424\u0443\u043D\u043A\u0446\u0438\u044F \u043F\u0440\u0438\u043D\u0430\u0434\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0438 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u0433\u043E \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0430 \u2014 \u043E\u0431\u043E\u0431\u0449\u0435\u043D\u0438\u0435 \u0438\u043D\u0434\u0438\u043A\u0430\u0442\u043E\u0440\u043D\u043E\u0439 (\u0438\u043B\u0438 \u0445\u0430\u0440\u0430\u043A\u0442\u0435\u0440\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043A\u043E\u0439) \u0444\u0443\u043D\u043A\u0446\u0438\u0438 \u043A\u043B\u0430\u0441\u0441\u0438\u0447\u0435\u0441\u043A\u043E\u0433\u043E \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0430. \u0412 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u0439 \u043B\u043E\u0433\u0438\u043A\u0435 \u043E\u043D\u0430 \u043F\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043B\u044F\u0435\u0442 \u0441\u0442\u0435\u043F\u0435\u043D\u044C \u043F\u0440\u0438\u043D\u0430\u0434\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0438 \u043A\u0430\u0436\u0434\u043E\u0433\u043E \u0447\u043B\u0435\u043D\u0430 \u043F\u0440\u043E\u0441\u0442\u0440\u0430\u043D\u0441\u0442\u0432\u0430 \u0440\u0430\u0441\u0441\u0443\u0436\u0434\u0435\u043D\u0438\u044F \u043A \u0434\u0430\u043D\u043D\u043E\u043C\u0443 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u043C\u0443 \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0443."@ru . . "\u0424\u0443\u043D\u043A\u0446\u0438\u044F \u043F\u0440\u0438\u043D\u0430\u0434\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0438 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u0433\u043E \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0430 \u2014 \u043E\u0431\u043E\u0431\u0449\u0435\u043D\u0438\u0435 \u0438\u043D\u0434\u0438\u043A\u0430\u0442\u043E\u0440\u043D\u043E\u0439 (\u0438\u043B\u0438 \u0445\u0430\u0440\u0430\u043A\u0442\u0435\u0440\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043A\u043E\u0439) \u0444\u0443\u043D\u043A\u0446\u0438\u0438 \u043A\u043B\u0430\u0441\u0441\u0438\u0447\u0435\u0441\u043A\u043E\u0433\u043E \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0430. \u0412 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u0439 \u043B\u043E\u0433\u0438\u043A\u0435 \u043E\u043D\u0430 \u043F\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043B\u044F\u0435\u0442 \u0441\u0442\u0435\u043F\u0435\u043D\u044C \u043F\u0440\u0438\u043D\u0430\u0434\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0438 \u043A\u0430\u0436\u0434\u043E\u0433\u043E \u0447\u043B\u0435\u043D\u0430 \u043F\u0440\u043E\u0441\u0442\u0440\u0430\u043D\u0441\u0442\u0432\u0430 \u0440\u0430\u0441\u0441\u0443\u0436\u0434\u0435\u043D\u0438\u044F \u043A \u0434\u0430\u043D\u043D\u043E\u043C\u0443 \u043D\u0435\u0447\u0451\u0442\u043A\u043E\u043C\u0443 \u043C\u043D\u043E\u0436\u0435\u0441\u0442\u0432\u0443."@ru . "\u0424\u0443\u043D\u043A\u0446\u0456\u044F \u043D\u0430\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0456 \u043D\u0435\u0447\u0456\u0442\u043A\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438 \u2014 \u0443\u0437\u0430\u0433\u0430\u043B\u044C\u043D\u0435\u043D\u043D\u044F \u0445\u0430\u0440\u0430\u043A\u0442\u0435\u0440\u0438\u0441\u0442\u0438\u0447\u043D\u043E\u0457 (\u0456\u043D\u0434\u0438\u043A\u0430\u0442\u043E\u0440\u043D\u043E\u0457) \u0444\u0443\u043D\u043A\u0446\u0456\u0457 \u043A\u043B\u0430\u0441\u0438\u0447\u043D\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438. \u0412 \u043D\u0435\u0447\u0456\u0442\u043A\u0456\u0439 \u043B\u043E\u0433\u0456\u0446\u0456 \u0432\u043E\u043D\u0430 \u044F\u0432\u043B\u044F\u0454 \u0441\u043E\u0431\u043E\u044E \u043A\u043E\u0436\u043D\u043E\u0433\u043E \u0447\u043B\u0435\u043D\u0430 \u043F\u0440\u043E\u0441\u0442\u043E\u0440\u0443 \u043C\u0456\u0440\u043A\u0443\u0432\u0430\u043D\u044C \u0434\u043E \u0434\u0430\u043D\u043E\u0457 \u043D\u0435\u0447\u0456\u0442\u043A\u043E\u0457 \u043C\u043D\u043E\u0436\u0438\u043D\u0438."@uk . "1119080668"^^ . . . . . . . "\u96B8\u5C6C\u51FD\u6578\uFF08membership function\uFF09\u4E5F\u7A31\u70BA\u6B78\u5C6C\u51FD\u6578\u6216\u6A21\u7CCA\u5143\u51FD\u6578\uFF0C\u662F\u6A21\u7CCA\u96C6\u5408\u4E2D\u6703\u7528\u5230\u7684\u51FD\u6578\uFF0C\u662F\u4E00\u822C\u96C6\u5408\u4E2D\u6307\u793A\u51FD\u6578\u7684\u4E00\u822C\u5316\u3002\u6307\u793A\u51FD\u6578\u53EF\u4EE5\u8AAA\u660E\u4E00\u500B\u96C6\u5408\u4E2D\u7684\u5143\u7D20\u662F\u5426\u5C6C\u65BC\u7279\u5B9A\u5B50\u96C6\u5408\u3002\u4E00\u5143\u7D20\u7684\u6307\u793A\u51FD\u6578\u7684\u503C\u53EF\u80FD\u662F0\u6216\u662F1\uFF0C\u800C\u4E00\u5143\u7D20\u7684\u96B8\u5C6C\u51FD\u6578\u6703\u662F0\u52301\u4E4B\u9593\u7684\u6578\u503C\uFF0C\u8868\u793A\u5143\u7D20\u5C6C\u65BC\u67D0\u6A21\u7CCA\u96C6\u5408\u7684\u300C\u771F\u5BE6\u7A0B\u5EA6\u300D\uFF08degree of truth\uFF09\u3002 \u4F8B\u5982\u8CEA\u6578\u70BA\u4E00\u96C6\u5408\uFF0C\u6574\u65783\u5C6C\u65BC\u8CEA\u6578\uFF0C\u5176\u6307\u793A\u51FD\u6578\u70BA1\uFF0C\u6574\u65784\u4E0D\u5C6C\u65BC\u8CEA\u6578\uFF0C\u5176\u6307\u793A\u51FD\u6578\u70BA0\u3002\u4F46\u91DD\u5C0D\u6A21\u7CCA\u96C6\u5408\uFF0C\u53EF\u80FD\u4E0D\u6703\u6709\u5982\u6B64\u660E\u78BA\u7684\u5B9A\u7FA9\uFF0C\u5047\u8A2D\u80D6\u5B50\u662F\u6A21\u7CCA\u96C6\u5408\uFF0C\u53EF\u80FD\u9AD4\u91CD80\u516C\u65A4\u7684\u4EBA\u5176\u96B8\u5C6C\u51FD\u6578\u70BA0.9\uFF0C\u9AD4\u91CD70\u516C\u65A4\u7684\u4EBA\u5176\u96B8\u5C6C\u51FD\u6578\u70BA0.8\u3002 \u96B8\u5C6C\u51FD\u6578\u6578\u503C\u662F\u57280\u52301\u4E4B\u9593\uFF0C\u770B\u4F3C\u985E\u4F3C\u6A5F\u7387\uFF0C\u4F46\u5169\u8005\u662F\u4E0D\u540C\u7684\u6982\u5FF5\u3002 \u96B8\u5C6C\u51FD\u6578\u6700\u65E9\u662F\u7531\u76E7\u83F2\u7279\u00B7\u6FA4\u5FB7\u57281965\u5E74\u7B2C\u4E00\u7BC7\u6709\u95DC\u6A21\u7CCA\u96C6\u5408\u7684\u8AD6\u6587\u4E2D\u63D0\u53CA\uFF0C\u4ED6\u5728\u6A21\u7CCA\u96C6\u5408\u7684\u8AD6\u6587\u4E2D\uFF0C\u63D0\u51FA\u7528\u503C\u57DF\u57280\u52301\u4E4B\u9593\u7684\u96B8\u5C6C\u51FD\u6578\uFF0C\u91DD\u5C0D\u5B9A\u7FA9\u57DF\u4E2D\u6240\u6709\u7684\u6578\u503C\u5B9A\u7FA9\u3002"@zh . . . "Funci\u00F3n miembro (matem\u00E1tica)"@es . . "\u0424\u0443\u043D\u043A\u0446\u0456\u044F \u043D\u0430\u043B\u0435\u0436\u043D\u043E\u0441\u0442\u0456"@uk . . "In mathematics, the membership function of a fuzzy set is a generalization of the indicator function for classical sets. In fuzzy logic, it represents the degree of truth as an extension of valuation. Degrees of truth are often confused with probabilities, although they are conceptually distinct, because fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition. Membership functions were introduced by Aliasker Zadeh in the first paper on fuzzy sets (1965). Aliasker Zadeh, in his theory of fuzzy sets, proposed using a membership function (with a range covering the interval (0,1)) operating on the domain of all possible values."@en . . . . . "Funkcja przynale\u017Cno\u015Bci"@pl . . . . "In mathematics, the membership function of a fuzzy set is a generalization of the indicator function for classical sets. In fuzzy logic, it represents the degree of truth as an extension of valuation. Degrees of truth are often confused with probabilities, although they are conceptually distinct, because fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition. Membership functions were introduced by Aliasker Zadeh in the first paper on fuzzy sets (1965). Aliasker Zadeh, in his theory of fuzzy sets, proposed using a membership function (with a range covering the interval (0,1)) operating on the domain of all possible values."@en . . . . . . . . "En matem\u00E1ticas, la funci\u00F3n de pertenencia de un conjunto borroso es una generalizaci\u00F3n de la funci\u00F3n indicadora para conjuntos cl\u00E1sicos. En l\u00F3gica borrosa, representa el como una extensi\u00F3n de la . Los grados de verdad a menudo se confunden con las probabilidades, aunque son conceptualmente distintos, porque la verdad borrosa representa la pertenencia a conjuntos vagamente definidos, no la probabilidad de alg\u00FAn evento o condici\u00F3n. Las funciones de pertenencia fueron introducidas por Zadeh en el primer art\u00EDculo sobre conjuntos borrosos (1965). Zadeh, en su teor\u00EDa de conjuntos borrosos, propuso utilizar una funci\u00F3n de pertenencia (con un rango que cubre el intervalo [0,1]) que opera en el dominio de todos los valores posibles."@es . . . . . . "Funkcja przynale\u017Cno\u015Bci - uog\u00F3lniona posta\u0107 funkcji charakterystycznej zbioru, okre\u015Blona na zbiorach rozmytych. W zbiorach klasycznych przyjmuje warto\u015B\u0107 1, gdy element w pe\u0142ni nale\u017Cy do zbioru albo 0, gdy nie nale\u017Cy wcale. W teorii zbior\u00F3w rozmytych element mo\u017Ce nale\u017Ce\u0107 do zbioru w pewnym stopniu, wi\u0119c funkcja przynale\u017Cno\u015Bci mo\u017Ce przyjmowa\u0107 warto\u015Bci z ca\u0142ego przedzia\u0142u jednostkowego [0,1]."@pl . "En matem\u00E1ticas, la funci\u00F3n de pertenencia de un conjunto borroso es una generalizaci\u00F3n de la funci\u00F3n indicadora para conjuntos cl\u00E1sicos. En l\u00F3gica borrosa, representa el como una extensi\u00F3n de la . Los grados de verdad a menudo se confunden con las probabilidades, aunque son conceptualmente distintos, porque la verdad borrosa representa la pertenencia a conjuntos vagamente definidos, no la probabilidad de alg\u00FAn evento o condici\u00F3n. Las funciones de pertenencia fueron introducidas por Zadeh en el primer art\u00EDculo sobre conjuntos borrosos (1965). Zadeh, en su teor\u00EDa de conjuntos borrosos, propuso utilizar una funci\u00F3n de pertenencia (con un rango que cubre el intervalo [0,1]) que opera en el dominio de todos los valores posibles."@es . . . . . . . . . "Funkcja przynale\u017Cno\u015Bci - uog\u00F3lniona posta\u0107 funkcji charakterystycznej zbioru, okre\u015Blona na zbiorach rozmytych. W zbiorach klasycznych przyjmuje warto\u015B\u0107 1, gdy element w pe\u0142ni nale\u017Cy do zbioru albo 0, gdy nie nale\u017Cy wcale. W teorii zbior\u00F3w rozmytych element mo\u017Ce nale\u017Ce\u0107 do zbioru w pewnym stopniu, wi\u0119c funkcja przynale\u017Cno\u015Bci mo\u017Ce przyjmowa\u0107 warto\u015Bci z ca\u0142ego przedzia\u0142u jednostkowego [0,1]."@pl . "Membership function (mathematics)"@en . .