Aytaç Altan

Research Statement

AI generated · Oct 24, 2026

Aytaç Altan's indexed work centers on hybrid forecasting and control systems that pair metaheuristic optimization with neural networks. His most-cited first-author studies include wind speed forecasting via LSTM combined with decomposition methods and grey wolf optimization (599 citations) and model predictive control of a three-axis gimbal for real-time UAV target tracking (553 citations). Related first-author work applies chaotic bio-inspired signal processing to digital currency forecasting (388 citations) and combines curvelet transforms with swarm optimization and deep learning for COVID-19 recognition from X-ray images (359 citations). As senior author, Altan has extended this line to AI-based plant disease detection in agricultural environments (284 citations) and crude oil prediction using LSTM with chaotic Henry gas solubility optimization (255 citations). A middle-author contribution applies wrapper-based feature selection with multi-objective optimization to chaotic crude oil time series (480 citations). His later senior-author work addresses diabetic retinopathy classification and solder paste defect detection. No software, datasets, patents, or grants appear in the indexed record, so the throughline is methodological: optimization-driven hybrid models applied across energy, aerospace, agriculture, and medical imaging.

Most Cited Works

Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques

Aytaç Altan, Seçkin Karasu, Stelios D. Bekiros

Chaos Solitons & Fractals2019

388Citations

Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique

Aytaç Altan, Seçkin Karasu

Chaos Solitons & Fractals2020

359Citations

Research Areas

Advanced Control Systems DesignStock Market Forecasting MethodsAerospace Engineering and Control SystemAdvanced DC-DC ConvertersMetaheuristic Optimization Algorithms Re

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Research Statement

Most Cited Works

Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques

Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique

Research Areas

Artificial Intelligence-Based Robust Hybrid Algorithm Design and Implementation for Real-Time Detection of Plant Diseases in Agricultural Environments

Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization

Overcoming Nonlinear Dynamics in Diabetic Retinopathy Classification: A Robust AI-Based Model with Chaotic Swarm Intelligence Optimization and Recurrent Long Short-Term Memory