Diverse Interdisciplinary Research Innovations

This study aims to compare the accuracy performances of different machine learning algorithms (Logistic Regression, Decision Tree, Support Vector Machines (SVMs), Random Forest, Artificial Neural Network, and XGBoost) using World Happiness Index data. The study is based on the 2024 World Happiness Report data and empl…

• BİLGE DOĞANLI

This study aims to compare the accuracy performances of different machine learning algorithms (Logistic Regression, Decision Tree, Support Vector Machines (SVMs), Random Forest, Artificial Neural Network, and XGBoost) using World Happiness Index data. The study is based on the 2024 World Happiness Report data and empl…

• SADULLAH ÇELİK

This study aims to compare the accuracy performances of different machine learning algorithms (Logistic Regression, Decision Tree, Support Vector Machines (SVMs), Random Forest, Artificial Neural Network, and XGBoost) using World Happiness Index data. The study is based on the 2024 World Happiness Report data and empl…

This study aims to compare the accuracy performances of different machine learning algorithms (Logistic Regression, Decision Tree, Support Vector Machines (SVMs), Random Forest, Artificial Neural Network, and XGBoost) using World Happiness Index data. The study is based on the 2024 World Happiness Report data and empl…

• MAHMUT ÜNSAL ŞAŞMAZ

The new priority in the grey modelling is to build new models that have more accurate forecasting power than the previous ones. This paper aims to develop the prediction performance of the existing continuous grey models. Therefore, a novel continuous grey model (OCCFGM(1,1)) is proposed with conformable fractional de…

• ZAFER ÖZTÜRK

The new priority in the grey modelling is to build new models that have more accurate forecasting power than the previous ones. This paper aims to develop the prediction performance of the existing continuous grey models. Therefore, a novel continuous grey model (OCCFGM(1,1)) is proposed with conformable fractional de…

• HALİS BİLGİL
• ÜMMÜGÜLSÜM ERDİNÇ

No abstract yet.

The aim of this study is to examine the multidimensional effects of AI-based feedback in learner-centered and collaborative learning environments among university students. The study employed a five-group experimental design: two individual learning groups receiving either AI-based feedback(G1) or human expert feedbac…

The aim of this study is to examine the multidimensional effects of AI-based feedback in learner-centered and collaborative learning environments among university students. The study employed a five-group experimental design: two individual learning groups receiving either AI-based feedback(G1) or human expert feedbac…

• HATİCE YILDIZ DURAK

The study analyzes coal consumption using the ECFGM(1, 1) model by utilizing time series data provided by the Statistical Review of World Energy for the years 2016-2019. The optimal α value, determined using the Brute Force Algorithm, is utilized to establish the model’s parameters and formulate the solution function.…

• ÜMMÜGÜLSÜM ERDİNÇ

No abstract yet.

• İBRAHİM ŞANLIBABA

A novel nonhomogeneous multivariable grey forecasting model termed NHMGM(1, m, kp, c) is proposed in this paper for use in nonhomogeneous multivariable exponential data sequences. The NHMGM(1, m, kp, c) model is able to reflect the nonlinear relation of the data sequences in the system, and it is proved that many clas…

• MEHMET TAMER ŞENEL