神经网络模型
2016-12-15 09:26:23 0 举报仅支持查看
AI智能生成
神经网络模型是一种模拟人脑神经元工作方式的计算模型,它由多个层次的节点(或称为“神经元”)组成,每个节点都与其他节点相连,并具有权重和偏置。信息从输入层传递到输出层,中间可以有任意数量的隐藏层。每个节点会对输入进行加权求和,然后通过一个激活函数进行处理,产生输出。这个输出又作为下一层节点的输入,如此反复,直到得到最终的输出结果。神经网络模型能够自动学习和提取数据的特征,广泛应用于机器学习和人工智能领域,如图像识别、语音识别、自然语言处理等。
方法
模版推荐
作者其他创作
大纲/内容
结构
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" alt="">
输入输出层神经元之间完全相连
输入输出<br>
输入表示在较优排序中排在第i 个位置的作业序号
输出表示在较优排序中排在第i +1个位置的作业序号
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAARIAAABICAIAAAC1N+1RAAAOQElEQVR4nO1dPYjkyBWu1HCRwYHiSTubyOdEUQdep4dhsQXuwBMMODiMoIM1izFcINNweOHMYEFzx8LCUDCwLF4GxMCxyYA4DMPRiEuGpREcyzE0Co5mKMpBVan1U/+t0vbs1hd2q/SqpPpUr169qg9gDw8PQ4D3XQEPj4cHTxsPD2N42nh4GMPTxsPDGJ42Hh7G8LTRx7bMYRJ9GsG377smHkPgPk+OpnH6Mi+3pkW1aIOKdAp6CObZBplX9mECrbP5NIgSmJeNNhMiTQAAAEzjNCsqnQdiWKoqMgjheRIF4CjJ79VVLXOYRAEAAIAwTrOi0qiTbVua1oIwTrNi85BsoTJfxiGYzrO1UVfWH222ZfY0pISJFtflR8MYjPFdnjwC4SJvvd3NKp0F9ROvbtJoEkTLlaIHmJVCxXIWn8E0Jk9eTZvqJo0mIHyalVuMUbVaRsEkSm9UzLFrC7l/EM4vS8RuEszSlbw3H5otVOWLEDxK8jvprVowcNLYmDOZwdsD48xdvnjmbuhDRToFwTRdNceZNTwN2j+iNZwFIJhB8YfLrhTG+C2MjtS0QbdwNgHgs7T4uW1R/sosa0WuAdO02BW7hbMJCE7hWuT2HKQttEqnQevmKujTBm2yeXCQvhlaw9kjgzYb4r6EJwActaY0mywOQLuDYozfZfGx7LNiVwpjjKs8CVW0YS+o8/qJUUn3sqwVuaDzNaF1EHLgMG0R2oATWKpdYAJ92vxcpJ8BAII40/EoxwO6hbPj9gMdFqTLNmlDPmO9DkoJ1v99n1LNOkhpQ4eaoPcoyEjV/32vWtHPf7dTYlzCCPB+P2RblGAuaEMZKXr67weovF7GUwCO4+ydMyP0QTe+F9Rl6n9B7vPkSPgi7UoRaNCG9qH+o6BlBZ3Srlas8/VdD1qM208O1BadfWjFWyh0acMmNs2Goaq4ghCeJ7NHdb2rIkvjEID2xIteCdM4JC+PXQZAEMawFdyoissk4rjj1Nlgz47MfduhPTeU7jk/9OPEMyfsu7alKJS0YZXk9Dxxt7OvFXF1uFQU9teDtUWJFMGyZ1sETdr0Jzb1e9rVAJWX85D9tqsWazbp2vHlevUiWbwuKkSius1mo/LySZycxdP+YyK87Twg7o+Do/M1Yl+QI84CDn0lnLdlV4pBSRvqQvM8DUYb3rfcslbU9eB2NdqV+738YG0R2pgMNrq0oV2/10HfZfEx5VJ1k0ZhtHhTIvIK24+ANn4SfZEky108tDWIVTfLxas1Yj2g9Sx49+T/2ETdYzQg+diQTxerDxvlea+k/q/3DuxKMShpwzwxnoPObh8meTcQbVkr9hfvobGa9Iodrq1NFmuuiTHo0YYOeb0xdBe5u8uTU7ZmRDjWvph9M7pxj+adqx/LCgkoSn7kRkUkU4KBsMniYOc0etp8aLQha5LddTkZjLIEuh2ULWj87y2MZ/WaGmVI62LpHdq/cynamdhIfhwe2zU8PWqwXfZKqANgSBtxKYZ9aFMPuYa0kdRK1pWZ42TUld+/rW15/Ww262SBCKFDG67XhNn0ZhJ98XR2sutVlAmti1mIvevjiadMLTJwi4vuOSiqIkufxos3ZW+W5ec2iq78cOY2jWK3cDbR8dY0aCMMPVNnLJx+3lhKI725czHPbcOYtxbEWx3iV0A5sdkb93lyxFuDo+Mh55WwtyWJpBmWotCPpPVpwxgli6SZ1oqFefpdufbGhdGtw7SFqgLG0Xw52Ggjn9iAIEyuG2M/b74h8qaq6yRsu3P0nk1b23WWzqNJ9548V3B4oDJfzqP461aSLHtbYk+MVyu7UhTqdRvWG/qemHTdxrJWjIrCYrJx4/BsoWq1jI4keTpdKGkjzKmh70ljviEIE9OUoSbrevdE1eoVzF40A1kSQz0MEknbruFp0JovirxW+Wq3XSkCnSwBkVMgzxKwrJVosipduT9UW2iVToNhI2mi0DPXGeMyROBNkaGG1x13xas8TfMN557o7vxPvwTgF5/87hvthAh7bLI4aA+qfNKKfNH9SmFslJPWfVPK74tlrbgXqCacB2nLwbqNyEPjB39Jvz+Osx+r777NaXV5V5I1/m7idztjD91efFkv4wTTdIWqfAnJN+KHf336CQAAgN+flz+tll9fOQ2mtddtMMajZ0Dr0MZnQFvaIrQxii1JaVOtIFmwB709G8Ql6FCZzUw+T1++rKdWlHiTKHldVAhjVBWvk2gCwjnsbDNiS6IzWKxzuEherHbLOMfx5XdXy5c0YYde+SsA/vCf83+nJjslLMDPWSIpDnTrEaoKGIdBI6WI7PQA3WbKS9GMoX7CEZkENt634EqSqBFEz67LLcabAs7D1rsbtFZ0C9YkIpFG0lt2n0IrW6JSTmxR0NnO/jlp/O2czSwY/nSFJA20NrHRKx9Hj+u0mzBOL7gBC9b4IEou6z2Jd3nyqMG6+sffAgAA+PXf3vyk21ZLMG+YM/nZFFkak3yi7s5PUm3Ac6/FpRg9dkNuvWrRmYb1r6yxy/frVWqoWu2AqiJL629rAhuxEytbslKD22IgcySTBUDXZwm4CxOT3myQ7G2LPZvwFp58aeA1E5TwRPPbp3/lmLXa39aYpei3ycl+Gys4DBOPTBvewpkG0BqezE0XZLdrOJ9rbYXQv3LMWu1va9RSNNh4QKMNZzI9FEajDfEzbWiDyjeLOMnMDkbZltdfxU8uNVbd9K8cs1b72xq1FMb04z5cSGBf0CB1ez10KIxHGxq0MUn1w3izWi4WmhlONaqbZfJMq5D+lWPWan9bo5Yi2K7haSCLyHHgkDZs+83Dpw2uDz3RTfXzeBgg4RP1CThduKFNnX7XCMINHRUgtHG/a2CHTZG98McLfjhwfbzg4YGlvgJgPVn38LDGA6WNh8f7hKeNh4cxPG08PIzhaePhYQxPGw8PY3jaeHgYw9NmUFAFlrEWYT2GhfZKjjltUJlfnLP8bZqOfc7fCPBxAZWX8/C4ndBupX9kpetkI5k0liHDIpsiu4DweRJNdPbADNxwPaEoE9rQOwZhfLajCT2yGTApoo8V1XUSHrXTiKz0j2x0nawkk0YyZFgErdLZPIVndIeMajurm4arhaK0j04v3yyiiUBHjW4SUu3sVRup8rPEoXaAO1tkc0F/N7Lh7l+rXc02G4bHMmS1mRnvtgbKD09w13CVUJTeqZw0KVPMP7bzeS+hNXQLZ7ORcswGtkWSfRpTGhv9IztdJwvJpNEMWck5YYy1Niq7bLhKKEpNG8YZOSUkagqa2K7haeBkZ457W93tgVb6R1a6TjaSSWMZspJzolDSxm3DVUJRKtpQS0oHjNHG7kRmOmsaRarNiS3y3Ovzfaz0j2x0nawkk0YyZCfn1L5ESBu3DVcKRclpw76aah3dPm02xeUi4rjynYOq2LEbTUzTAjlQkhLakrZMC22HwUb/yE7XyUIyaTRDVnJOdVUUtHHbcKVQlPzAp945QyLUG2yIYbTOnsyTM9LLeYfQck+K2v3oUEmKX4F9QQ9GJG/Z6txuq7PPbY4VH8uQ1ZHnu6rIaeO44coDByW0qYcaDWVM+n0ldd2sll9drLfcM0h5egT8H90oSfVtDXLgbeuMUishFyuBGhvtl7EMWenSdEuLLnDdcJVQlJg2nQFEhnr4I/2mKssKyyQ3uNGP3gfYiZKUwNa+QJtsXu9H97SxrVuv9PuijUooSkyb1gAivApj3DjcrdlHJV25M3zxjwB2oiSldeCyOdAtnIVacmtC/SMrXScbyaSxDFnJOXVL29BmqIbLhKKEtKkP5lRHnBjBWsPCvqJoLpSkXAiwoarI0vm8fxCpn9s83LlNwxBfKEpEm47fJUFdm1a0jSfjwddO4E9snChJiWzZ4z5Pjvrrgzb6R3a6ThaSSaMZspJzYtCNpDlsuEwoSjnaKGjDVp06pzpxujJaX6Xzx715heCoWBdKUm5O1kXl9TI+iZfN4cZG/8hK18lGMmksQ1ZyTp1LhLRx3XCFUJRybiPtZGwxtHv0Xr8rV99D+BoK1Z75E5uBlaT4toaIpKFbODtu1MpK/8hK18lGMmksQ1ZyThTqLAGnDVcJRUkC0GyiL3RpanWEbu5zryvf5enzfPM9Z8GEP6q4UJJyqixNHICGm2oTkLCbj1lIJo1myErOCWNskJPmpOH7rNvUDhgvGw2V14soAIBJqXAqx/i2XV+ku2WcaVqgu3z5spXFQNICVufp1bvGExlASer+h2/+8tf4j8EJLO8FtgZBP67tM6Bt64Yx1tOccddwpVCUPLmG7EYAAEwbvjs5nHIiVAupR4AZfLvO4WKxXG0aRH+1unoBadffjRV3ZbZImcs5mJLUf//+GxJEP4Flxbc1DFpZAqxuNlpLUl2nxuuAq0b9JZJJoiKjGbKSc6o9HUqAIW+uUs7CWIO0GhsHqiI7Z1vhAOnNz6FsO2fdyKaWE9n6A4JocblrA/2xrQM1rJLUlh0VveXaGgjEOe6Hzqy0loS6TuxxcXx3kWSSpMhohozknOrVlSb+/Pz1P4e4ubLhDCqhqAM8S2DYeNcoJ6zvI+Njo7V0X8InvXDQ4EXGNKQp5+T05k07CqGow6PNwEpSY9LGwoqV1hK6hSf/MAtsWBQZ0ZCunJPTm7egEIo6PNoMrCQ1jp4HGSFNrVhpLaHyejF/Ij0gYoAiIxrSlXNyevNuMYVQ1KHRZnAlqZFkcNAazgKTattoLaFq9SJZQBNhCYsiYxrSlHNyevM+1EJRh0UbB0pSo6lHsTNQEtO363FI0BOKOhjauFKSGll0jUQd/fGCDxMOjxd8YBhfdM3jw8eHTRsvuubhBB82bTw8nMDTxsPDGJ42Hh7G8LTx8DCGp42HhzH+D2RNWwPJ2sNHAAAAAElFTkSuQmCC" alt="">
NNMM矩阵<br>(神经网络主矩阵)<br>
矩阵元素的变化<img src="data:image/png;base64,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" alt="">
N*N维矩阵<br>
DM矩阵:m 个作业对应行和列交叉位置上的元素
过程<br>
NNMM——DM——可能的排序——分析各排序Cmax——minCmax为最优排序<br>
范例<br>
<img 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" 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子主题
DM矩阵:<img src="data:image/png;base64,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" alt="">
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