我正在為遺傳算法構(gòu)建一個(gè)模擬輪盤選擇函數(shù)。首先，我會(huì)想加起來(lái)sum的fitnessScore主功能。加起來(lái)后，fitnessScore我想sum使用math/randGo 中的包隨機(jī)化一個(gè)值。在這種情況下我應(yīng)該如何使用 rand 包如何修復(fù)spin_wheel := rand.sum以隨機(jī)化一個(gè)值？package mainimport( "fmt" "time" "math/rand")func rouletteWheel(fitnessScore []float64) []float64{ sum := 0.0 for i := 0; i < len(fitnessScore); i++ { sum += fitnessScore[i] } rand.Seed(time.Now().UnixNano()) spin_wheel := rand.sum partial_sum := 0.0 for i := 0; i < len(fitnessScore); i++{ partial_sum += fitnessScore[i] if(partial_sum >= spin_wheel){ return fitnessScore } } return fitnessScore}func main(){ fitnessScore := []float64{0.1, 0.2, 0.3, 0.4} fmt.Println(rouletteWheel(fitnessScore))}
1 回答
千萬(wàn)里不及你
TA貢獻(xiàn)1784條經(jīng)驗(yàn) 獲得超9個(gè)贊
例如，
package main
import (
"fmt"
"math/rand"
"time"
)
// Returns the selected weight based on the weights(probabilities)
// Fitness proportionate selection:
// https://en.wikipedia.org/wiki/Fitness_proportionate_selection
func rouletteSelect(weights []float64) float64 {
// calculate the total weights
sum := 0.0
for _, weight := range weights {
sum += weight
}
// get a random value
value := rand.Float64() * sum
// locate the random value based on the weights
for _, weight := range weights {
value -= weight
if value <= 0 {
return weight
}
}
// only when rounding errors occur
return weights[len(weights)-1]
}
func main() {
rand.Seed(time.Now().UnixNano())
weights := []float64{0.1, 0.2, 0.3, 0.4}
fmt.Println(rouletteSelect(weights))
}
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