本项目中实现了灰色理论机器学习（マシンラーニング）。这种理论可用于大数据分析（データ分析）、用户行为分析（ユーザーの行動分析）以及数据挖掘（データマイニング），特别是通过大数据找出对真实结果有影响的小部件。
KRGreyTheory 可以用于设置神经网络权重/偏置的预处理。
platform :ios, '8.0'
pod "KRGreyTheory", "~> 1.2.0"#import "KRGreyTheory.h"KRGreyGM1N *gm1n = [[KRGreyTheory sharedTheory] useGM1N];
[gm1n addPatterns:@[@2.0f, @11.0f, @1.5f, @2.0f, @2.2f, @3.0f] patternKey:@"x1"];
[gm1n addPatterns:@[@3.0f, @13.5f, @1.0f, @3.0f, @3.0f, @4.0f] patternKey:@"x2"];
[gm1n addPatterns:@[@2.0f, @11.0f, @3.5f, @2.0f, @3.0f, @2.0f] patternKey:@"x3"];
[gm1n addPatterns:@[@4.0f, @12.0f, @2.0f, @1.0f, @2.0f, @1.0f] patternKey:@"x4"];
[gm1n addPatterns:@[@1.0f, @10.0f, @5.0f, @2.0f, @1.0f, @1.0f] patternKey:@"x5"];
[gm1n analyze];
[gm1n print];KRGreyGM0N *gm0n = [[KRGreyTheory sharedTheory] useGM0N];
[gm0n addPatterns:@[@1.0f, @1.0f, @1.0f, @1.0f, @1.0f, @1.0f] patternKey:@"x1"];
[gm0n addPatterns:@[@0.75f, @1.22f, @0.2f, @1.0f, @1.0f, @1.0f] patternKey:@"x2"];
[gm0n addPatterns:@[@0.5f, @1.0f, @0.7f, @0.66f, @1.0f, @0.5f] patternKey:@"x3"];
[gm0n addPatterns:@[@1.0f, @1.09f, @0.4f, @0.33f, @0.66f, @0.25f] patternKey:@"x4"];
[gm0n addPatterns:@[@0.25f, @0.99f, @1.0f, @0.66f, @0.33f, @0.25f] patternKey:@"x5"];
[gm0n analyze];
[gm0n print];KRGreyGM11 *gm11 = [[KRGreyTheory sharedTheory] useGM11];
[gm11 addPattern:@533.0f patternKey:@"x1"];
[gm11 addPattern:@665.0f patternKey:@"x2"];
[gm11 addPattern:@655.0f patternKey:@"x3"];
[gm11 addPattern:@740.0f patternKey:@"x4"];
[gm11 forecast]; // To forecast x5 that number
[gm11 print];V1.2.0
MIT。