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Prediction of Wind Speed by Using Machine Learning

Buket İşler

Due to the depletion of fossil fuel resources and environmental concerns caused by traditional fuel systems in recent years, the share of renewable energy sources in current energy production has been increasing. Among these energy sources, wind and solar energy stand out compared to other sources. Wind energy is a clean, sustainable and low-cost energy source. Wind and solar energies vary considerably according to the stochastic environment of meteorological conditions. Solar and wind energy variability and uncontrollability lead to power quality, generation-consumption balance and reliabilit ...Daha fazlası

Konferans Kağıdı 2023 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)14104 , pp. 7 - 86 17 Görüntülenme

Süresiz Ambargo

Fishier mantis optimiser: a swarm intelligence algorithm for clustering images of COVID-19 pandemic

Cevat Rahebi

In this study, an automated segmentation method is used to increase the speed of diagnosis and reduce the segmentation error of CT scans of the lung. In the proposed technique, the fishier mantis optimiser (FMO) algorithm is modelling and formulated based on the intelligent behaviour of mantis insects for hunting to create an intelligent algorithm for image segmentation. In the second phase of the proposed method, the proposed algorithm is used to cluster scanned image images of COVID-19 patients. Implementation of the proposed technique on CT scan images of patients shows that the similarity ...Daha fazlası

Makale 2023 International Journal of Nanotechnology20 ( 1-4 ) , pp. 2 - 45 26 Görüntülenme Süresiz Ambargo

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Text‑based automatic personality prediction: a bibliographic review

Taymaz Akan

Personality detection is an old topic in psychology and automatic personality prediction (or perception) (APP) is the automated (computationally) forecasting of the personality on diferent types of human generated/exchanged contents (such as text, speech, image, and video). The principal objective of this study is to ofer a shallow (overall) review of natural language processing approaches on APP since 2010. With the advent of deep learning and following it transfer-learning and pre-trained model in NLP, APP research area has been a hot topic, so in this review, methods are categorized into th ...Daha fazlası

Makale 2022 Journal of Computational Social Science5 ( 2 ) , pp. 1 - 1593 95 Görüntülenme

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Multilevel image thresholding with multimodal optimization

Taymaz Akan

Thresholding method is one of the most popular approaches for image segmentation where an objective function is defined in terms of threshold numbers and their locations in a histogram. If only a single threshold is considered, a segmented image with two classes is achieved. On the other hand, multiple classes in the output image are created with multilevel thresholding. Otsu and Kapur's procedures have been conventional steps for defining objective functions. Nevertheless, the fundamental problem with thresholding techniques is the determination of threshold numbers, which must be selected by ...Daha fazlası

Makale 2021 Multimedia Tools and Applications80 ( 10 ) , pp. 1 - 15289 121 Görüntülenme Süresiz Ambargo

Süresiz Ambargo

MPPT Design for PV-Powered WPT System with Irregular Pulse Density Modulation

Güngör Bal

—Electric vehicles (EVs) are well-known as environmentally friendly systems. Therefore, the demand for EVs is rapidly increasing every day, but for charging batteries of EVs eco-friendly electrical energy sources are needed. To use a clean energy source, this article proposes a wireless power transfer (WPT) system energized by photovoltaic panels. In this study, pulse density modulation technique controlled with incremental conductance algorithm is preferred in the WPT system for both transferring power from primary to secondary windings and for tracking maximum power point (MPP). The proposed ...Daha fazlası

Makale 2023 Taylor and Francis Ltd.51 ( 1 ) , pp. 8 - 91 82 Görüntülenme Süresiz Ambargo

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Battle Royale Optimizer for solving binary optimization problems

Taymaz Akan

Battle Royale Optimizer (BRO) is a recently proposed metaheuristic optimization algorithm used only in continuous problem spaces. The BinBRO is a binary version of BRO. The BinBRO algorithm employs a differential expression, which utilizes a dissimilarity measure between binary vectors instead of a vector subtraction operator, used in the original BRO algorithm to find the nearest neighbor. To evaluate BinBRO, we applied it to two popular benchmark datasets: the uncapacitated facility location problem (UFLP) and the maximum-cut (Max-Cut) graph problems from OR-Library. An open-source MATLAB im ...Daha fazlası

Makale 2022 Software Impacts12 105 Görüntülenme

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Smart energy meter with GSM card recharge

Cevat Rahebi

The objective of the project are to reduce delays at energy metre billing counters and automatically limit energy meter usage, if the bill is not paid. The study also seeks to provide a mechanism that will lessen the amount of money lost to power theft and other illicit activities. The method of work takes a completely novel idea for a prepaid energy meter. GSM technology is employed in order for the customer to get notifications regarding your power usage (measured in watts); if it hits the minimum, it would immediately notify the user that they require a recharge. This method works well for ...Daha fazlası

Makale 2024 JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES45 ( 2 ) , pp. 4 - 496 12 Görüntülenme

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Detection of cyber-attacks on smart grids using improved VGG19 deep neural network architecture and Aquila optimizer algorithm

Cevat Rahebi

This study introduces an innovative smart grid (SG) intrusion detection system, integrating Game Theory, swarm intelligence, and deep learning (DL) to protect against complex cyber-attacks. This method balances training samples by employing conditional DL using Game Theory and CGAN. The Aquila optimizer (AO) algorithm selects features, mapping them onto the dataset and converting them into RGB color images for training a VGG19 neural network. AO optimizes meta-parameters, enhancing VGG19 accuracy. Testing on the NSL-KDD dataset generates remarkable results: 99.82% accuracy, 99.69% sensitivity, ...Daha fazlası

Makale 2024 Signal, Image and Video Processing18 ( 2 ) , pp. 1 - 1491 19 Görüntülenme

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3D Path Planning Method for Multi-UAVs Inspired by Grey Wolf Algorithms

Mohammed Ahmed Shah

Efficient and collision-free pathfinding, between source and destination locations for multi-Unmanned Aerial Vehicles (UAVs), in a predefined environment is an important topic in 3D Path planning methods. Since path planning is a Non-deterministic Polynomial-time (NP-hard) problem, metaheuristic approaches can be applied to find a suitable solution. In this study, two efficient 3D path planning methods, which are inspired by Incremental Grey Wolf Optimization (I-GWO) and Expanded Grey Wolf Optimization (Ex-GWO), are proposed to solve the problem of determining the optimal path for UAVs with mi ...Daha fazlası

Makale 2021 Journal Of Internet Technology22 ( 4 ) , pp. 7 - 755 100 Görüntülenme Süresiz Ambargo

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A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process

Tolga Kudret Karaca

The stochastic skiving stock problem (SSP), a relatively new combinatorial optimization problem, is considered in this paper. The conventional SSP seeks to determine the optimum structure that skives small pieces of different sizes side by side to form as many large items (products) as possible that meet a desired width. This study studies a multiproduct case for the SSP under uncertain demand and waste rate, including products of different widths. This stochastic version of the SSP considers a random demand for each product and a random waste rate during production. A two-stage stochastic pro ...Daha fazlası

Makale 2023 Applied Computational Intelligence and Soft Computing2023 27 Görüntülenme

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Ambulance Vehicle Routing in Smart Cities Using Artificial Neural Network

Cevat Rahebi

This work proposes a routing ambulance vehicles method that uses the neural network. For the input of the neural network, eight features are selected. These features depend on the time, the position of the accident, ambulance and hospital, number of streets and injured person, type of accident, and age of the patient. With these features, the Ambulance can be decided to select the minimum route to find the nearest hospital. In this paper, we evaluate crucial metrics in responding to the accident, such as establishing temporary emergency units, the number of available ambulance units, and the c ...Daha fazlası

Kitap Bölümü 2022 International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2022 91 Görüntülenme Süresiz Ambargo

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Enhancing Fault Detection and Classification in MMC-HVDC Systems: Integrating Harris Hawks Optimization Algorithm with Machine Learning Methods

Cevat Rahebi

Accurate fault detection in high-voltage direct current (HVDC) transmission lines plays a pivotal role in enhancing operational efciency, reducing costs, and ensuring grid reliability. Tis research aims to develop a cost-efective and high-performance fault detection solution for HVDC systems. Te primary objective is to accurately identify and localize faults within the power system. In pursuit of this goal, the paper presents a comparative analysis of current and voltage characteristics between the rectifer and inverter sides of the HVDC transmission system and their associated alternating cur ...Daha fazlası

Makale 2024 International Transactions on Electrical Energy Systems2024 20 Görüntülenme