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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