نوع مقاله : مقاله پژوهشی

نویسندگان

1 هیئت علمی، گروه مهندسی علوم خاک، دانشگاه زابل، ایران

2 هیئت علمی، گروه مهندسی علوم خاک، دانشگاه زابل ، ایران

3 دانشجوی کارشناسی ارشد، گروه مهندسی علوم خاک، دانشگاه زابل ، ایران

چکیده

یک مطالعه مقایسه­ای با هدف بررسی کارایی شبکه عصبی مصنوعی (ANN) و رگرسیون خطی چندمتغیره (MLR) برای پیش­بینی پایداری خاکدانه­های بزرگتر از 25/0 میلی­متر در روش الک تر(250SAW>) در کاربری­های مختلف منطقه میانکنگی سیستان انجام شد. بدین منظور تعداد 140 نمونه خاک از اراضی کشاورزی، مرتعی و بایر منطقه تهیه و برخی ویژگی­های خاک از جمله بافت، ماده آلی، کربنات کلسیم، سدیم تبادلی، کلسیم و منیزیم محلول، اسیدیته، هدایت الکتریکی و  شاخص پایداری خاکدانه در آن­ها اندازه­گیری شد. در مناطق بایر و مرتعی میزان کلسیم و منیزیم محلول و در زمین­های زیر کشت مقدار سدیم تبادلی بیشترین همبستگی خطی را با پایداری خاکدانه نشان دادند و مدل­های رگرسیونی توسعه­یافته توانستند 56-49 درصد از تغییرات SAW را در کاربری­های مختلف منطقه توجیه نمایند. در شبکه عصبی پرسپترون به کار گرفته شده  متغیر اسمی نوع کاربری همزمان با سایر ورودی­ها وارد مدل گردید که این مدل توانست نزدیک به 90 درصد تغییرات شاخص پایداری را در مجموعه آزمون پیش­بینی کند. نتایج کمی کردن اهمیت متغیرها به روش ارتباط وزنی در روش شبکه عصبی نشان داد که عامل نوع کاربری و نوع و مقدار کاتیون­های فاز تبادلی و محلول خاک بیشترین سهم را در تغییرپذیری شاخص پایداری خاکدانه در منطقه مورد مطالعه دارند.

کلیدواژه‌ها

عنوان مقاله [English]

Predicting Aggregate Stability using Soil Properties in Different Land Use

نویسندگان [English]

  • A Shabani 1
  • A Gholamalizadeh Ahangar 2
  • S Golshahi 3
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