c – 未声明的标识符？
作者：互联网
继续使用代码出错,这是从旧版VS到2010版的转换：
#include <string>
#include <stdlib.h>
#include <iostream>
#include <time.h>
#include <math.h>
using std::string;
#define CROSSOVER_RATE 0.7
#define MUTATION_RATE 0.001
#define POP_SIZE 100 //must be an even number
#define CHROMO_LENGTH 300
#define GENE_LENGTH 4
#define MAX_ALLOWABLE_GENERATIONS 400
//returns a float between 0 & 1
#define RANDOM_NUM ((float)rand()/(RAND_MAX+1))
//----------------------------------------------------------------------------------------
//
// define a data structure which will define a chromosome
//
//----------------------------------------------------------------------------------------
struct chromo_typ
{
//the binary bit string is held in a std::string
string bits;
float fitness;
chromo_typ(): bits(""), fitness(0.0f){};
chromo_typ(string bts, float ftns): bits(bts), fitness(ftns){}
};
/////////////////////////////////prototypes/////////////////////////////////////////////////////
void PrintGeneSymbol(int val);
string GetRandomBits(int length);
int BinToDec(string bits);
float AssignFitness(string bits, int target_value);
void PrintChromo(string bits);
void PrintGeneSymbol(int val);
int ParseBits(string bits, int* buffer);
string Roulette(int total_fitness, chromo_typ* Population);
void Mutate(string &bits);
void Crossover(string &offspring1, string &offspring2);
//-------------------------------main--------------------------------------------------
//
//-------------------------------------------------------------------------------------
int main()
{
//seed the random number generator
srand((int)time(NULL));
//just loop endlessly until user gets bored :0)
while (true)
{
//storage for our population of chromosomes.
chromo_typ Population[POP_SIZE];
//get a target number from the user. (no error checking)
float Target;
cout << "\nInput a target number: ";
cin >> Target;
cout << endl << endl;
//first create a random population, all with zero fitness.
for (int i=0; i<POP_SIZE; i++)
{
Population[i].bits = GetRandomBits(CHROMO_LENGTH);
Population[i].fitness = 0.0f;
}
int GenerationsRequiredToFindASolution = 0;
//we will set this flag if a solution has been found
bool bFound = false;
//enter the main GA loop
while(!bFound)
{
//this is used during roulette wheel sampling
float TotalFitness = 0.0f;
// test and update the fitness of every chromosome in the
// population
for (int i=0; i<POP_SIZE; i++)
{
Population[i].fitness = AssignFitness(Population[i].bits, Target);
TotalFitness += Population[i].fitness;
}
// check to see if we have found any solutions (fitness will be 999)
for (i=0; i<POP_SIZE; i++)
{
if (Population[i].fitness == 999.0f)
{
cout << "\nSolution found in " << GenerationsRequiredToFindASolution << " generations!" << endl << endl;;
PrintChromo(Population[i].bits);
bFound = true;
break;
}
}
// create a new population by selecting two parents at a time and creating offspring
// by applying crossover and mutation. Do this until the desired number of offspring
// have been created.
//define some temporary storage for the new population we are about to create
chromo_typ temp[POP_SIZE];
int cPop = 0;
//loop until we have created POP_SIZE new chromosomes
while (cPop < POP_SIZE)
{
// we are going to create the new population by grabbing members of the old population
// two at a time via roulette wheel selection.
string offspring1 = Roulette(TotalFitness, Population);
string offspring2 = Roulette(TotalFitness, Population);
//add crossover dependent on the crossover rate
Crossover(offspring1, offspring2);
//now mutate dependent on the mutation rate
Mutate(offspring1);
Mutate(offspring2);
//add these offspring to the new population. (assigning zero as their
//fitness scores)
temp[cPop++] = chromo_typ(offspring1, 0.0f);
temp[cPop++] = chromo_typ(offspring2, 0.0f);
}//end loop
//copy temp population into main population array
for (i=0; i<POP_SIZE; i++)
{
Population[i] = temp[i];
}
++GenerationsRequiredToFindASolution;
// exit app if no solution found within the maximum allowable number
// of generations
if (GenerationsRequiredToFindASolution > MAX_ALLOWABLE_GENERATIONS)
{
cout << "No solutions found this run!";
bFound = true;
}
}
cout << "\n\n\n";
}//end while
return 0;
}
//---------------------------------GetRandomBits-----------------------------------------
//
// This function returns a string of random 1s and 0s of the desired length.
//
//-----------------------------------------------------------------------------------------
string GetRandomBits(int length)
{
string bits;
for (int i=0; i<length; i++)
{
if (RANDOM_NUM > 0.5f)
bits += "1";
else
bits += "0";
}
return bits;
}
//---------------------------------BinToDec-----------------------------------------
//
// converts a binary string into a decimal integer
//
//-----------------------------------------------------------------------------------
int BinToDec(string bits)
{
int val = 0;
int value_to_add = 1;
for (int i = bits.length(); i > 0; i--)
{
if (bits.at(i-1) == '1')
val += value_to_add;
value_to_add *= 2;
}//next bit
return val;
}
//---------------------------------ParseBits------------------------------------------
//
// Given a chromosome this function will step through the genes one at a time and insert
// the decimal values of each gene (which follow the operator -> number -> operator rule)
// into a buffer. Returns the number of elements in the buffer.
//------------------------------------------------------------------------------------
int ParseBits(string bits, int* buffer)
{
//counter for buffer position
int cBuff = 0;
// step through bits a gene at a time until end and store decimal values
// of valid operators and numbers. Don't forget we are looking for operator -
// number - operator - number and so on... We ignore the unused genes 1111
// and 1110
//flag to determine if we are looking for an operator or a number
bool bOperator = true;
//storage for decimal value of currently tested gene
int this_gene = 0;
for (int i=0; i<CHROMO_LENGTH; i+=GENE_LENGTH)
{
//convert the current gene to decimal
this_gene = BinToDec(bits.substr(i, GENE_LENGTH));
//find a gene which represents an operator
if (bOperator)
{
if ( (this_gene < 10) || (this_gene > 13) )
continue;
else
{
bOperator = false;
buffer[cBuff++] = this_gene;
continue;
}
}
//find a gene which represents a number
else
{
if (this_gene > 9)
continue;
else
{
bOperator = true;
buffer[cBuff++] = this_gene;
continue;
}
}
}//next gene
// now we have to run through buffer to see if a possible divide by zero
// is included and delete it. (ie a '/' followed by a '0'). We take an easy
// way out here and just change the '/' to a '+'. This will not effect the
// evolution of the solution
for (i=0; i<cBuff; i++)
{
if ( (buffer[i] == 13) && (buffer[i+1] == 0) )
buffer[i] = 10;
}
return cBuff;
}
//---------------------------------AssignFitness--------------------------------------
//
// given a string of bits and a target value this function will calculate its
// representation and return a fitness score accordingly
//------------------------------------------------------------------------------------
float AssignFitness(string bits, int target_value)
{
//holds decimal values of gene sequence
int buffer[(int)(CHROMO_LENGTH / GENE_LENGTH)];
int num_elements = ParseBits(bits, buffer);
// ok, we have a buffer filled with valid values of: operator - number - operator - number..
// now we calculate what this represents.
float result = 0.0f;
for (int i=0; i < num_elements-1; i+=2)
{
switch (buffer[i])
{
case 10:
result += buffer[i+1];
break;
case 11:
result -= buffer[i+1];
break;
case 12:
result *= buffer[i+1];
break;
case 13:
result /= buffer[i+1];
break;
}//end switch
}
// Now we calculate the fitness. First check to see if a solution has been found
// and assign an arbitarily high fitness score if this is so.
if (result == (float)target_value)
return 999.0f;
else
return 1/(float)fabs((double)(target_value - result));
// return result;
}
//---------------------------------PrintChromo---------------------------------------
//
// decodes and prints a chromo to screen
//-----------------------------------------------------------------------------------
void PrintChromo(string bits)
{
//holds decimal values of gene sequence
int buffer[(int)(CHROMO_LENGTH / GENE_LENGTH)];
//parse the bit string
int num_elements = ParseBits(bits, buffer);
for (int i=0; i<num_elements; i++)
{
PrintGeneSymbol(buffer[i]);
}
return;
}
//--------------------------------------PrintGeneSymbol-----------------------------
//
// given an integer this function outputs its symbol to the screen
//----------------------------------------------------------------------------------
void PrintGeneSymbol(int val)
{
if (val < 10 )
cout << val << " ";
else
{
switch (val)
{
case 10:
cout << "+";
break;
case 11:
cout << "-";
break;
case 12:
cout << "*";
break;
case 13:
cout << "/";
break;
}//end switch
cout << " ";
}
return;
}
//------------------------------------Mutate---------------------------------------
//
// Mutates a chromosome's bits dependent on the MUTATION_RATE
//-------------------------------------------------------------------------------------
void Mutate(string &bits)
{
for (int i=0; i<bits.length(); i++)
{
if (RANDOM_NUM < MUTATION_RATE)
{
if (bits.at(i) == '1')
bits.at(i) = '0';
else
bits.at(i) = '1';
}
}
return;
}
//---------------------------------- Crossover ---------------------------------------
//
// Dependent on the CROSSOVER_RATE this function selects a random point along the
// lenghth of the chromosomes and swaps all the bits after that point.
//------------------------------------------------------------------------------------
void Crossover(string &offspring1, string &offspring2)
{
//dependent on the crossover rate
if (RANDOM_NUM < CROSSOVER_RATE)
{
//create a random crossover point
int crossover = (int) (RANDOM_NUM * CHROMO_LENGTH);
string t1 = offspring1.substr(0, crossover) + offspring2.substr(crossover, CHROMO_LENGTH);
string t2 = offspring2.substr(0, crossover) + offspring1.substr(crossover, CHROMO_LENGTH);
offspring1 = t1; offspring2 = t2;
}
}
//--------------------------------Roulette-------------------------------------------
//
// selects a chromosome from the population via roulette wheel selection
//------------------------------------------------------------------------------------
string Roulette(int total_fitness, chromo_typ* Population)
{
//generate a random number between 0 & total fitness count
float Slice = (float)(RANDOM_NUM * total_fitness);
//go through the chromosones adding up the fitness so far
float FitnessSoFar = 0.0f;
for (int i=0; i<POP_SIZE; i++)
{
FitnessSoFar += Population[i].fitness;
//if the fitness so far > random number return the chromo at this point
if (FitnessSoFar >= Slice)
return Population[i].bits;
}
return "";
}
我得到的错误是：
error C2065: 'cin' : undeclared identifier
error C2065: 'cout' : undeclared identifier
error C2065: 'endl' : undeclared identifier
error C2065: 'i' : undeclared identifier
error C2228: left of '.bits' must have class/struct/union
error C2228: left of '.fitness' must have class/struct/union
解决方法:
使用std或使用namespace std声明每个cin,cout(std :: cin,std :: cout)的前缀;在开始.
// check to see if we have found any solutions (fitness will be 999)
for (i=0; i<POP_SIZE; i++)
//copy temp population into main population array
for (i=0; i<POP_SIZE; i++) // In both cases, You forgot to declare i. So, change to
// for (int i=0; ...)
标签：c,algorithm,visual-studio,genetic-algorithm 来源： https://codeday.me/bug/20190723/1516026.html