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models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
per algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search), search algorithm (Expand Search)
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Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants
Published 2006“…This paper presents novel technique for adaptive tracking of a class of nonlinear dynamic plants based on a new control oriented model known as U-model. …”
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Autopilot Design and Commercial Autopilot Evaluation Using Flybarless Helicopter
Published 2014Get full text
doctoralThesis -
304
Minimizing using BBO and DFO methods
Published 2022“…The goal of this thesis is to develop two MATLAB codes for the numerical algorithm of [1]. To solve nonlinear differential equations we use Runge-Kutta method of fourth order, and for the minimization part, we use two different methods, namely Nelder-Mead and Model Based Descent methods. …”
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masterThesis -
305
Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023“…A higher level of accuracy (99%) was found in studies that used support vector machine, decision trees, and k-means clustering algorithms. </p><h3>Conclusions </h3><p dir="ltr">This review presents an overview of studies based on AI models and algorithms used to predict and diagnose pancreatic cancer patients. …”
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Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone
Published 2021“…Nonetheless, the performance analysis section will be executed using the algorithmic big-O notation. The results show that these protocols are verifiably protected in the ROM and ROR model using the CDHP.…”
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On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity
Published 2020“…We de ne the constraints of the problem, model it as a Markov Decision Process, and propose a reinforcement learning-based solution to optimize the UAV trajectory. …”
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masterThesis -
310
Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction
Published 2024“…Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory motion. …”
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. …”
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313
Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
Published 2013Get full text
doctoralThesis -
314
Development of a deep learning-based group contribution framework for targeted design of ionic liquids
Published 2024“…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”
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315
On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. The purpose of this work is to provide a systematic comparison of various nature-inspired algorithms across both low-cost analytical and high-fidelity simulation-driven design problems.…”
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Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT)
Published 2015“…Looking at the historical data of students, fuzzy logic can be used to develop rules based on these data. Genetic Algorithm would be used to optimize the performance of the system.…”
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. Our objective in this work is to propose machine learning models that can benefit from the historical data available in banking environment in order to improve and automate their business processes. …”
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masterThesis