代码搜索：Best 开发教程
找到约 10,000 项符合「Best 开发教程」的源代码
代码结果 10,000
www.eeworm.com/read/111801/15503250
c sha2speed.c
/*
* FILE: sha2speed.c
* AUTHOR: Aaron D. Gifford
*
* Copyright (c) 2000-2001, Aaron D. Gifford
* All rights reserved.
*
* Redistribution and use in source and bin
www.eeworm.com/read/106899/15618404
out art002.out
BEST NEURON:0
IN: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
OUT: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Top Down weights:
1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Bottom up weights:
0.200000 0.200000 0.200000 0.20000
www.eeworm.com/read/106899/15618407
out art001.out
BEST NEURON:0
IN: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
OUT: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Top Down weights:
1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Bottom up weights:
0.200000 0.200000 0.200000 0.20000
www.eeworm.com/read/105943/15653293
url 新软件工程联盟chinaswe.yeah.net.url
[InternetShortcut]
URL=http://best.163.com/~netsoft/
Modified=6055C63945DFBF0198
www.eeworm.com/read/104053/15711565
c w.c
/* w - show what logged in users are doing. Almost entirely rewritten from
* scratch by Charles Blake circa June 1996. Some vestigal traces of the
* original may exist. That was done in 1993 by L
www.eeworm.com/read/100773/15864502
py yappsrt.py
# Yapps 2.0 Runtime
#
# This module is needed to run generated parsers.
from string import *
import re
class SyntaxError:
"When we run into an unexpected token, this is the exception to use"
www.eeworm.com/read/390064/8487598
m main.m
%TSP问题蚁群算法
global NC; %迭代次数
global city_n; %城市数量
global dis_table; %城市距离矩阵
global G; %记录进化代数
global everbest; %历代最优解
global hu_table; %启发式分布表
global adapt_best;
%======
www.eeworm.com/read/470452/6910825
m elitist.m
%--------------------------------------------------
% 最优保存策略
%--------------------------------------------------
function [new_gen,curbest_indiv,curbest_fitness] = el
www.eeworm.com/read/380669/6966858
m main.m
%TSP问题蚁群算法
global NC; %迭代次数
global city_n; %城市数量
global dis_table; %城市距离矩阵
global G; %记录进化代数
global everbest; %历代最优解
global hu_table; %启发式分布表
global adapt_best;
%======
www.eeworm.com/read/198334/7940043
m main.m
%TSP问题蚁群算法
global NC; %迭代次数
global city_n; %城市数量
global dis_table; %城市距离矩阵
global G; %记录进化代数
global everbest; %历代最优解
global hu_table; %启发式分布表
global adapt_best;
%======