Vol. 11 No. 1 (2023)

View Vol. 11 No. 1 (2023)

This issue of International Journal of Applied Methods in Electronics and Computers (Vol. 11, No. 1, 2023) features advancements in hybrid recommendation systems, CNN-based classification, and machine learning applications in industrial diagnostics and energy analysis. Topics include risk clustering, tea disease detection, defect prediction in steel plates, genetic algorithm-optimized neural networks, and real-time battery management on FPGA platforms.

Published: 31-03-2023

Research Articles

  • A Novel Article Recommendation System Empowered by the Hybrid Combinations of Content-Based State-of-the-Art Methods

    Ilya KUŞ, Sinem BOZKURT KESER, Savaş OKYAY
    1-12
    DOI: https://doi.org/10.18100/ijamec.1199886

  • Clustering Application and Evaluation of the Countries' Word Risk and Climate Risk Indices

    Nazmiye ELIGÜZEL, Sena AYDOĞAN, Ibrahim Miraç ELIGÜZEL
    13-19
    DOI: https://doi.org/10.18100/ijamec.1217399

  • A Manhattan distance based hybrid recommendation system

    Begüm UYANIK, Günce Keziban ORMAN
    20-29
    DOI: https://doi.org/10.18100/ijamec.1232090

  • Classification of tea leaves diseases by developed CNN, feature fusion, and classifier based model

    Nadide YÜCEL, Muhammed YILDIRIM
    30-36
    DOI: https://doi.org/10.18100/ijamec.1235611

  • Detection of Defects in Rolled Stainless Steel Plates by Machine Learning Models

    Ahmet FEYZIOĞLU, Yavuz Selim TASPINAR
    37-43
    DOI: https://doi.org/10.18100/ijamec.1253191

  • A Genetic Algorithm Optimized ANN for Prediction of Exergy and Energy Analysis Parameters of a Diesel Engine Different Fueled Blends

    Ali YAŞAR
    44-54
    DOI: https://doi.org/10.18100/ijamec.1262259

  • FPGA-Based battery management system for real-time monitoring and instantaneous SOC prediction

    Abdulkadir SADAY, Ilker Ali OZKAN, Ismail SARITAS
    55-61
    DOI: https://doi.org/10.18100/ijamec.1233451