نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی عمران، دانشکده فنی و مهندسی، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران

2 دانشیار، گروه مهندسی عمران، دانشکده فنی و مهندسی، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران

3 استادیار، گروه مهندسی شیمی، دانشکده فنی و مهندسی، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران

چکیده

اندازه­گیری مستقیم منحنی نگهداشت آب خاک، پرزحمت، وقت­گیر و هزینه­بر می­باشد، لذا از مدل­های ریاضی و فن‌های بهینه­سازی برای برآورد پارامترهای آن استفاده می‌شود. در این پژوهش، روش I-JAYA برای حل مسئله بهینه­سازی معرفی و توسعه داده شد. برای بررسی کارایی این روش، 12 نمونه خاک با 6 بافت متفاوت از 9 منطقه مختلف دنیا مورداستفاده قرار گرفت. بدین منظور، ابتدا با به‌کارگیری الگوریتم ژنتیک و مدل­های متداول ریاضی مسئله بهینه­سازی حل‌شده و با استفاده از نمودارهایTaylor ، متوسط شاخص ضریب تعیین و زمان محاسباتی، مناسب‌ترین مدل انتخاب شد. مدل ریاضی Fredlund-Xing  در حالت دو-وجهی و مدل Brooks-Corney به‌ترتیب با متوسط ضریب تعیین 913/0و 825/0، بهترین و بدترین نتایج این مرحله را ارائه دادند. سپس با استفاده از مناسب‌ترین مدل، مسئله بهینه­سازی با الگوریتم‌های DE، SSA، JAYA و هم­چنین I-JAYA حل شده و مقادیر متوسط ضریب تعیین به‌ترتیب 919/0، 931/0، 921/0 و 958/0 به‌دست آمد. نتایج حاکی از ارتقا 16% متوسط شاخص ضریب تعیین، با انتخاب مدل مناسب ریاضی و همچنین استفاده از روش I-JAYA می­باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigation of Mathematical Model and Development of I-JAYA Method to Optimally Estimate the Parameters of Soil Water Retention Curve

نویسندگان [English]

  • Reza Askary 1
  • Mohsen Najarchi 2
  • Hossein Mazaheri 3

1 PhD Scholar, Department of Civil Engineering, Faculty of Engineering, Arak Branch, Islamic Azad University, Arak, Iran

2 Assoc. Professor, Department of Civil Engineering, Faculty of Engineering, Arak Branch, Islamic Azad University, Arak, Iran

3 Assist. Professor, Department of Chemical Engineering, Faculty of Engineering, Arak Branch, Islamic Azad University, Arak, Iran

چکیده [English]

Direct soil water retention curve (SWRC) measurement is laborious, time-consuming, and expensive. To estimate its parameters, mathematical models and optimization approaches are applied. In this study, an improved alternative method to solve the optimization problem was introduced and developed. To evaluate the efficiency of this method, 12 soil samples with 6 different textures from 9 different regions of the world were used. The optimization equations were solved using a genetic algorithm (GA) and standard mathematical models, and the best model was chosen based on Taylor diagrams, R2, and computing time. The Bimodal versions of Fredlund-Xing (FX-b) and Brooks-Corney (BC) mathematical models represented the best and poorest findings of this stage, with R2 values of 0.913 and 0.825, respectively. Then, the optimization problem is solved with differential evolution (DE), Salp Swarm Algorithm (SSA), Jaya, and improved Jaya (I-Jaya) method, and the mean values of R2 were obtained 0.919, 0.931, 0.921, and 0.958, respectively. The results indicated a 16% improvement in the average R2, by selecting the suitable mathematical model and also using the I-Jaya.

کلیدواژه‌ها [English]

  • Matric Potential
  • Meta-heuristic Algorithms
  • Optimization
  • Soil Texture
  • Statistical Parameters
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