پیش بینی الگوی توزیع سوسک پوست خوار کاج، (Orthotomicus erosus (Coleoptera: Curculionidae: Scolytinae با استفاده از زمین‌آمار و شبکة عصبی مصنوعی

نوع مقاله: مقاله کامل، فارسی

نویسندگان

گروه گیاهپزشکی، دانشکده کشاورزی، دانشگاه رازی، کرمانشاه، ایران.

چکیده

سوسک­ پوست­خوار کاج، (Orthotomicus erosus (Wollaston) (Coleoptera: Curculionidae: Scolytinae، یکی از مهم­ترین آفات درختان کاج می­ باشد. حمله و تغذیة این سوسک­ها بافت­های آوند آبکش را در زیر پوست درختان آلوده تخریب و عبور شیرة گیاهی را مختل نموده و باعث مرگ درختان آلوده می­شود. این پژوهش به منظور پیش‌بینی الگوی توزیع و ترسیم نقشة پراکنش O. erosus با استفاده از شبکه‌های عصبی پرسپترون چند لایه (MLP)، شبکة عصبی MLP ترکیب شده با الگوریتم ژنتیک و شبکة عصبی MLP ترکیب شده با الگوریتم رقابت استعماری در سطح شهر کرمانشاه انجام شد. داده‌های مربوط به جمعیت این آفت از طریق نمونه­ برداری از درختان کاج در مناطق مختلف شهر کرمانشاه در سال­های 1393 و 1394 به­ دست آمد. برای ارزیابی قابلیت شبکه‌های عصبی مورد استفاده در پیش‌بینی توزیع آفت از مقایسة آماری پارامترهایی مانند واریانس، میانگین و توزیع آماری بین مقادیر پیش‌بینی شدة مکانی توسط شبکة عصبی MLP ترکیب شده با الگوریتم ژنتیک و الگوریتم رقابت استعماری و مقادیر واقعی آن‌ها استفاده شد. نتایج نشان داد که در فازهای آموزش و آزمایش، مقادیر پارامترهای مذکور بین داده‌های واقعی و پیش‌بینی شدة آفت تفاوت معنی‌داری را نشان نداد که نشان‌دهندة دقت بالا و نیز قابلیت شبکه‌های عصبی به منظور ترسیم نقشة پراکندگی این آفت در سطح شهر کرمانشاه می­باشد. مقادیر ضریب تبیین (R2) نشان داد که الگوریتم رقابت استعماری، دقت بالاتری در تخمین تراکم O. erosus نسبت به دو روش دیگر داشته است. همچنین مقایسة مقادیر ضریب تبیین بین شبکه­های عصبی مختلف و روش زمین‌آمار نشان داد که هر سه مدل شبکة عصبی الگوی توزیع سوسک پوست‌خوار را نسبت به روش زمین‌آمار بهتر پیش ­بینی کردند. روش زمین آمار و نقشه‌های ترسیم شده توسط شبکه ­های عصبی نشان داد که توزیع این آفت به صورت تجمعی است. نتایج حاصل از روش زمین‌آمار نیز نشان­ دهندة توزیع تجمعی آفت می­باشد. 

کلیدواژه‌ها


عنوان مقاله [English]

Predicting distribution pattern of the Mediterranean pine engraver, Orthotomicus erosus (Coleoptera: Curculionidae: Scolytinae), by geostatistics and artificial neural network

نویسندگان [English]

  • Najmeh Shirvani Farsani
  • Abbas Ali Zamani
  • Samad jamali
Dept. of Plant Protection, College of Agriculture, Razi University, Kermanshah, Iran.
چکیده [English]

The Mediterranean pine engraver, Orthotomicus erosus (Wollaston) (Coleoptera: Curculionidae: Scolytinae), is one of the most important pests of pine trees in Kermanshah. Attack and feeding of this pest destroy the floem tissues under the bark of the infected trees and disrupt the plant sap flow, causing the death of infected trees. The purpose of this study was to predict and mapping the distribution of O. erosus using multi-layer perceptron neural networks combined with genetic and imperialist competitive algorithms in Kermanshah. The sampling of pine trees was done in 2015-2016 in Kermanshah. To evaluate the ability of the used neural networks to predict the distribution was used statistical comparison the parameters such as mean, variance and statistical distribution between actual and predicted values by multi-layer perceptron neural networks combined with genetic and imperialist competitive algorithms. Results showed that in training and test phases, was no significant differences between average, variance and statistical distribution of actual and predicted data that indicates the high accuracy and the ability of neural networks to map the distribution of this pest in Kermanshah. The R2 values revealed that imperialist competitive algorithm had a higher accuracy to estimate the density of O. erosus compared with the other two methods. In addition, the comparison of the coefficients of the R2 between different neural networks and geostatistics method showed that all three neural network models predicted the distribution pattern of O. erosus better than the geostatistics method. The maps drawn by all three neural networks showed that the distribution of this pest was cumulative. The results obtained from the geostatistics method represented the cumulative distribution of the pest.

کلیدواژه‌ها [English]

  • Genetic algorithm
  • imperialist competitive algorithm
  • Kriging
  • spatial distribution

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