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双代号网络图计算软件介绍
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&&& &&&一种应用最广泛的网络计划图。
【双代号网络图计算基本介绍】
&&& &&&网络计划技术是一种计划管理方法，在工业、农业、国防和复杂的科学研究等计划管理中有着广泛的应用。网络计划技术是以网络图的形式制定计划，求得计划的最优方案，并据以组织和控制生产，达到预定目标的一种科学管理方法。其中双代号网络图以其包含因素多，能够准确反映关键线路，是一种应用最广泛的网络计划图。《双代号网
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用common lisp语言写的一个神经网络（后附源代码2）收藏
;接在上一贴 “用common lisp语言写的一个神经网络（后附源代码1）”之后;;************************************************************;;************************************************************;;************************************************************;;************************************************************;;***************神经网络权值修改模块*************************;;单个节点修改权值、参数为对象及调整系数(defun modify-weights-nodex (object-nodex adjust-ratio)
(nodex-weighted object-nodex ) (+
(nodex-weighted object-nodex )
(* adjust-ratio (nodex-weighted
object-nodex )))))(defun modify-weights-nodey (object-nodey adjust-ratio)
(nodey-weighted object-nodey ) (+
(nodey-weighted object-nodey )
(* adjust-ratio (nodey-weighted
object-nodey )))))(defun modify-weights-neurons (object-neurons
adjust-ratio)
(neurons-weighted object-neurons ) (+
(neurons-weighted object-neurons )
adjust-ratio (neurons-weighted
object-neurons ))))
(neurons-threshold object-neurons ) (+
(neurons-threshold
object-neurons )
adjust-ratio (neurons-threshold
object-neurons ))))
(neurons-resting object-neurons ) (+
(neurons-resting
object-neurons )
adjust-ratio (neurons-resting
object-neurons ))))
(neurons-bias object-neurons ) (+
(neurons-bias
object-neurons )
adjust-ratio (neurons-bias
object-neurons )))));;修改整个神经元的权值、参数为调整系数(defun modify-weights-module (name
adjust-ratio )
(dolist (i
( find-multiple-nodex name) )
(modify-weights-nodex
i adjust-ratio ))
(dolist (j
( find-multiple-nodey name) )
(modify-weights-nodey
j adjust-ratio ))
(modify-weights-neurons
(find-neurons
name) adjust-ratio )
(setf (neurons-excitingtimes (find-neurons
name)) 0));;一个时间周期内神经网络中被激活的神经元数目(defun network-activation-num()
(reduce #'+ (let* (( list-activation-num-neurons
nil) )(dolist (obj *neurons-list* ) (setf
list-activation-num-neurons(append
list-activation-num-neurons (list (neurons-excitingtimes obj)))))list-activation-num-neurons )));;整个网络神经元在一个时间周期内的激活率(defun network-activation-rate()
(/ (network-activation-num)
(length *neurons-list*) *adjust-frequency*
));;单个神经元在一个时间周期内的激活率(defun neurons-activation-rate(obj)
(/ (neurons-excitingtimes obj)
*adjust-frequency*));;网络权值调整系数(defun
network-weight-change-rate-fn()
(cond ((& (network-activation-rate) 1/3)(- 0 (network-activation-rate)))((& (network-activation-rate) 2/3)(network-activation-rate))(t 0)));;单个神经元权值调整系数(defun
neurons-weight-change-rate-fn(object-neurons )
(cond ((& (neurons-activation-rate object-neurons ) 1/3)(- 0 (neurons-activation-rate object-neurons) ))((& (neurons-activation-rate object-neurons) 2/3)(neurons-activation-rate object-neurons) )( t 0)));;网络神经元综合调整系数(defun weights-comprehensive-regulation (object-neurons)
(network-weight-change-rate-fn)
(neurons-weight-change-rate-fn object-neurons )));;神经网络权值修改模块(defun
weights-change-network-module()
(unless (=
(network-weight-change-rate-fn) 0)
(Batch-adding-neurons
*new-neurons-number* *new-nodex-number*
*new-nodey-number* )
(repeat-matching-nodes ));节点重新分配
(dolist (obj *neurons-list* )
(unless (= (weights-comprehensive-regulation obj ) 0)
(modify-weights-module (neurons-name obj)(weights-comprehensive-regulation obj )))));;************************************************************;;************************************************************;;************************************************************;;************************************************************;;****************网络结构调整模块****************************;;置空感应器本身及其连接节点x的connectname和connecttype项(defun
nil-sensors-connect (object-sensors)
(let* ((i nil))
(setf i (find-nodex (sensors-connectname object-sensors)))
(setf (nodex-connectname i) nil)
(setf (nodex-connecttype i) nil))
(setf (sensors-connectname object-sensors) nil)
(setf (sensors-connecttype object-sensors) nil));;置空x节点本身及其连接节点y与感应器的connectname和connecttype项(defun
nil-nodex-connect (object-nodex)
(if (equal (nodex-connecttype object-nodex) &type-nodey&)
(nil-nodex-y-connect
object-nodex)
(nil-nodex-s-connect
object-nodex)))(defun
nil-nodex-s-connect (object-nodex)
(let* ((i nil))
(setf i (find-sensors (nodex-connectname object-nodex)))
(setf (sensors-connectname i) nil)
(setf (sensors-connecttype i) nil))
(setf (nodex-connectname object-nodex) nil)
(setf (nodex-connecttype object-nodex) nil))(defun
nil-nodex-y-connect (object-nodex)
(let* ((i nil))
(setf i (find-nodey (nodex-connectname object-nodex)))
(setf (nodey-connectname i) nil)
(setf (nodey-connecttype i) nil))
(setf (nodex-connectname object-nodex) nil)
(setf (nodex-connecttype object-nodex) nil));;置空y节点本身及其连接节点x与效应器的connectname和connecttype项(defun
nil-nodey-connect (object-nodey)
(if (equal (nodey-connecttype object-nodey) &type-nodex&)
(nil-nodey-x-connect
object-nodey)
(nil-nodey-e-connect
object-nodey)))(defun
nil-nodey-e-connect (object-nodey)
(let* ((i nil))
(setf i (find-effector (nodey-connectname object-nodey)))
(setf (effector-connectname i) nil)
(setf (effector-connecttype i) nil))
(setf (nodey-connectname object-nodey) nil)
(setf (nodey-connecttype object-nodey) nil))(defun
nil-nodey-x-connect (object-nodey)
(let* ((i nil))
(setf i (find-nodex (nodey-connectname object-nodey)))
(setf (nodex-connectname i) nil)
(setf (nodex-connecttype i) nil))
(setf (nodey-connectname object-nodey) nil)
(setf (nodey-connecttype object-nodey) nil));;置空感应器本身及其连接节点x的connectname和connecttype项(defun
nil-effector-connect (object-effector)
(let* ((i nil))
(setf i (find-nodey (effector-connectname object-effector)))
(setf (nodey-connectname i) nil)
(setf (nodey-connecttype i) nil))
(setf (effector-connectname object-effector) nil)
(setf (effector-connecttype object-effector) nil));;当各节点权值为零时要移除，并将断开的有效节点重新分配;;第一步：检测整个网络、当前节点权值为零时先置空与其相连的节点的connectname和connecttype项(defun
set-connect-nil()
(dolist (i (remove-if-not
#'(lambda (e) (equal (sensors-weighted e) 0)) *sensors-list*))
(equal (sensors-connectname i) nil)
(nil-sensors-connect i)))
(dolist (i (remove-if-not
#'(lambda (e) (equal (nodex-weighted e) 0)) *nodex-list*))
(equal (nodex-connectname i) nil)
(nil-nodex-connect i)))
(dolist (i (remove-if-not
#'(lambda (e) (equal (nodey-weighted e) 0)) *nodey-list*))
(equal (nodey-connectname i) nil)
(nil-nodey-connect i)))
(dolist (i (remove-if-not
#'(lambda (e) (equal (effector-weighted e) 0)) *effector-list*))
(equal (effector-connectname i) nil)
(nil-effector-connect i))));;第二步：检测整个网络、删除所有weighted项为零的节点(defun
delete-zero-weighte()
*sensors-list* (remove-if
#'(lambda (e)(equal
(sensors-weighted e) 0 ))
*sensors-list*))
*nodex-list* (remove-if
#'(lambda (e)(equal
(nodex-weighted e) 0 ))
*nodex-list*))
*nodey-list* (remove-if
#'(lambda (e)(equal
(nodey-weighted e) 0 ))
*nodey-list*))
*effector-list* (remove-if
#'(lambda (e)(equal
(effector-weighted e) 0 ))
*effector-list*))
*sensors-list* (remove-if
#'(lambda (e)(equal
(sensors-weighted e) 0 ))
*sensors-list*)));;第三步：检测整个网络、推送所有当前connectname或connecttype项为空（此时权值都不为零）的节点(defun
push-nil-connect()
(dolist (ii (remove-if-not
#'(lambda(e)(or (equal (sensors-connectname e) nil)
(equal (sensors-connecttype e) nil))) *sensors-list*))
(pushnew ii *undistribution-sensors-list*))
(dolist (jj (remove-if-not
#'(lambda(e)(or (equal (nodex-connectname e) nil)
(equal (nodex-connecttype e) nil))) *nodex-list*))
(pushnew jj *undistribution-nodex-list*))
(dolist (kk (remove-if-not
#'(lambda(e)(or (equal (nodey-connectname e) nil)
(equal (nodey-connecttype e) nil))) *nodey-list*))
(pushnew kk *undistribution-nodey-list*))
(dolist (ll (remove-if-not
#'(lambda(e)(or (equal (effector-connectname e) nil)
(equal (effector-connecttype e) nil))) *effector-list*))
(pushnew ll *undistribution-effector-list*)));;第四步：检测整个网络、删除所有connectname或connecttype项为空的节点(defun
delete-nil-connect()
(setf *sensors-list* (remove-if #'(lambda(e)(or (equal (sensors-connectname e) nil)
(equal (sensors-connecttype e) nil))) *sensors-list*))
(setf *nodex-list* (remove-if #'(lambda(e)(or (equal (nodex-connectname e) nil)
(equal (nodex-connecttype e) nil))) *nodex-list*))
(setf *nodey-list* (remove-if #'(lambda(e)(or (equal (nodey-connectname e) nil)
(equal (nodey-connecttype e) nil))) *nodey-list*))
(setf *effector-list* (remove-if #'(lambda(e)(or (equal (effector-connectname e) nil)
(equal (effector-connecttype e) nil))) *effector-list*)));;清理已经没有输入或输出节点的神经元;;删除与x节点相连的感应器与y节点(defun delete-failure-neurons-x( object-del-neurons)
(dolist (i (find-multiple-nodex
(neurons-name
object-del-neurons)))
(nodex-connecttype
&type-sensors&)
(delete-sensors (nodex-name
(delete-nodey
(nodex-name
(delete-subordinate-nodex
(neurons-name
object-del-neurons))
(delete-neurons
(neurons-name object-del-neurons)));;删除与y节点相连的效应器与x节点(defun delete-failure-neurons-y( object-del-neurons)
(dolist (i (find-multiple-nodey
(neurons-name
object-del-neurons)))
(nodey-connecttype
&type-effector&)
(delete-effector (nodey-name
(delete-nodex
(nodey-name
(delete-subordinate-nodey
(neurons-name
object-del-neurons))
(delete-neurons
(neurons-name object-del-neurons)));;当没有输入节点或者输出节点时删除神经元(defun delete-failure-neurons()
(dolist (obj-neurons *neurons-list* )
(if (equal (find-multiple-nodex
(neurons-name
obj-neurons)) nil)(delete-failure-neurons-y obj-neurons))
(if (equal (find-multiple-nodey
(neurons-name
obj-neurons)) nil)(delete-failure-neurons-x obj-neurons))));;网络结构调整模块(defun
structures-change-network-module()
(set-connect-nil)
(delete-zero-weighte)
(push-nil-connect)
(delete-nil-connect)
(repeat-matching-nodes );重新匹配节点
(delete-failure-neurons)
(Batch-adding-sensors
*new-sensors-number*)
(Batch-adding-effector *new-effector-number*)
(repeat-matching-nodes ));;************************************************************;;*****************神经网络节能运行模块***********************;;单个结构点置零、参数为对象(defun zero-sensors-command (object-sensors )
(sensors-command
object-sensors )
0 ))(defun zero-nodex-command (object-node )
(nodex-command
object-node )
0 ))(defun zero-neurons-command(object-neurons)
(neurons-command
object-neurons )
0 ))(defun zero-nodey-command (object-node )
(nodey-command
object-node )
0 ))(defun zero-effector-command (object-effector )
(effector-command
object-effector )
0 ));;点乘、单个节点加权、参数为对象
(defun dot-product-nodex-command (object-node )
(* (nodex-command
object-node )
(nodex-weighted
object-node )))
;;单个节点加权、参数为对象及线性输出值并设置Y的输出项data(defun dot-product-nodey-command (object-node command-value)
(nodey-command object-node ) (* (nonliner-fn
command-value)
(nodey-weighted
object-node ))));;输入加权求和函数并置零、参数为神经元名(defun input-weighted-sum-command (name )
(reduce #'+ (let* (( list-dot-product-nodex
nil) )(dolist (object-nodex
( find-multiple-nodex name) )
list-dot-product-nodex(append
list-dot-product-nodex
(list (dot-product-nodex object-nodex ) ))) (zero-nodex-command object-nodex))list-dot-product-nodex )));;************************数据输入***************************(defun sensors-&nodex-module-command()
(dolist (object-sensors *sensors-list*)
(setf (nodex-command (find-nodex
(sensors-connectname
object-sensors)))
(sensors-command object-sensors))
(zero-sensors-command object-sensors)));;******************神经元的数据处理**************************(defun nodex-&neurons-module-command(obj-neurons)
(setf (neurons-command obj-neurons) (+
(neurons-command obj-neurons)
(neurons-weighted obj-neurons)
(input-weighted-sum-command
(neurons-name obj-neurons))))))(defun neurons-&nodey-module-command(obj-neurons)
(dolist (i
( find-multiple-nodey (neurons-name obj-neurons)))
(dot-product-nodey-command
(neurons-command obj-neurons))));;***********************数据输出*************************(defun nodey-&effector-nodex-module-command()
(dolist (j
*nodey-list*)
(nodey-connecttype
&type-effector&)
(nodey-&effector-module-command
(nodey-&nodex-module-command
j))))(defun nodey-&effector-module-command (object-nodey)
(setf (effector-command
(find-effector
(nodey-connectname
object-nodey)))(nodey-command
object-nodey))
(zero-nodey-command
object-nodey))(defun nodey-&nodex-module-command (object-nodey)
(setf (nodex-command
(find-nodex
(nodey-connectname
object-nodey)))(+ (nodex-command
(find-nodex
(nodey-connectname
object-nodey)))
(nodey-command
object-nodey)))
(zero-nodey-command
object-nodey));;沉默开关模块(defun silent-switch-module()
(dolist (obj *neurons-list* )
(sensors-&nodex-module-command)
(nodex-&neurons-module-command
(when (& (neurons-command obj) 0)
(neurons-&nodey-module-command
(zero-neurons-command
(nodey-&effector-nodex-module-command)
(setf (neurons-keepsilent
obj) 0));不保持沉默
(if (& (neurons-command obj ) 0)(setf (neurons-keepsilent
obj) 1))));;************************************************************;;************************************************************;;************************************************************;;************************主函数******************************;;主函数(defun main ()
(dotimes (m *main-loop-number* )
(dotimes (n *adjust-frequency*);用来控制取样的周期
(output-asterisk) ;输出两行星号
(format t &main-loop-number: ~a ~%& (+ m
1));主循环的次数
(format t &Inner-loop-number: ~a ~%& (+ n
1));内循环的次数
(neurons-skeleton-network-module);神经骨架网络模块
(set-record);设置记录用于保存
(save-db *database-file-location*)
(terpri))(output-mailsymbol);;输出两行@号
(silent-switch-module);沉默开关
(weights-change-network-module );权值调整
(structures-change-network-module);结构调整
(system-information)
(set-record);设置记录用于保存
(save-db *database-file-location*)
(output-dollarsign)));;************************************************************;;************************************************************;;************************************************************;;************************************************************;;********************系统信息********************************;;系统信息(defun system-information()
(format t &sensors-number: ~a ~%& (length *sensors-list*))
(format t &effector-number: ~a ~%& (length *effector-list*))
(format t &neurons-number: ~a ~%& (length *neurons-list*))
(format t &nodex-number: ~a ~%& (length *nodex-list*))
(format t &nodey-number: ~a ~%& (length *nodey-list*))
&undistribution-nodex-number: ~a ~%& (length *undistribution-nodex-list*))
&undistribution-nodey-number: ~a ~%& (length *undistribution-nodey-list*))
&undistribution-sensors-number: ~a ~%& (length *undistribution-sensors-list*))
&undistribution-effector-number: ~a ~%& (length *undistribution-effector-list*)));;测试信息(defun test-neurons (obj-neurons)
(format t &neurons-name: ~a ~%&
(neurons-name obj-neurons));神经元的编号
(format t &neurons-rundeep: ~a ~%&
(neurons-rundeep obj-neurons));运行深度
(format t &neurons-delaytimevalue: ~a ~%&
(neurons-delaytimevalue obj-neurons));延时值
(format t &neurons-delaycounter: ~a ~%&
(neurons-delaycounter obj-neurons));延时计数器
(format t &neurons-keepsilent: ~a ~%&
(neurons-keepsilent obj-neurons));当前神经元的是否保持沉默
(format t &neurons-stata: ~a ~%&
(neurons-stata obj-neurons));当前神经元的状态值
(format t &neurons-excitingtimes: ~a ~%&
(neurons-excitingtimes obj-neurons));激活次数
(terpri))(defun test-x (name)
(let* ((x-data-list
nil) (x-weighted-list
(dolist (object-nodex
( find-multiple-nodex name) )
x-data-list
x-data-list
(list (nodex-data
object-nodex ) )))
x-weighted-list
x-weighted-list
(list (nodex-weighted
object-nodex )))))
(format t &x-data-list: ~a ~%& x-data-list)
(format t &x-weighted-list: ~a ~%& x-weighted-list)))(defun test-y (name)
(let* ((y-data-list
nil) (y-weighted-list
(dolist (object-nodey
( find-multiple-nodey name) )
y-data-list
y-data-list
(list (nodey-data
object-nodey ) )))
y-weighted-list
y-weighted-list
(list (nodey-weighted
object-nodey )))))
(format t &y-data-list: ~a ~%& y-data-list)
(format t &y-weighted-list: ~a ~%& y-weighted-list)));;输出两行星号(defun output-asterisk()
(dotimes (i 2)
(dotimes (j 60)
(format t &*&))
(format t &~%&)));;输出两行@号(defun output-mailsymbol()
(dotimes (i 2)
(dotimes (j 60)
(format t &@&))
(format t &~%&)));;输出几行%号(defun output-dollarsign()
(dotimes (i 5)
(dotimes (j 60)
(format t &!&))
(format t &~%&)))
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定制HR最喜欢的简历
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