Refine Search
Input a time range for publish date searching.
Article Types
Publication Year

Articles ( Showing 1-20 of 28 items)
Searched for: [ Keywords: "Ensemble learning" ] clear all
Open Access Journal Article
Ensemble Learning Approaches for Credit Risk Assessment in Financial Institutions
by Emma Anderson
Abstract
Abstract This paper explores the application of ensemble learning approaches in credit risk assessment within financial institutions. Credit risk assessment is a critical function in the financial sector, involving the evaluation of borrowers' creditworthiness to prevent defaults and ensure the stability of the financial system. Ensemble learning, which combines multiple models [...] Read more

Open Access Journal Article
Natural Language Processing for Sentiment Analysis in Social Media Data
by Sarah Brown
Abstract
This paper explores the application of Natural Language Processing (NLP) techniques in sentiment analysis of social media data. With the exponential growth of social media platforms, vast amounts of textual data are being generated daily. Analyzing the sentiment behind this data can provide valuable insights for businesses, policymakers, and researchers. The study delves into t [...] Read more

Open Access Journal Article
Intelligent Tutoring Systems for Adaptive Learning Environments
by Michael White
Abstract
This paper investigates the potential of Intelligent Tutoring Systems (ITS) in fostering adaptive learning environments. ITS are computer-based applications designed to assist learners in acquiring knowledge and skills by adapting to their individual needs and learning styles. The increasing use of technology in education has opened up new avenues for personalized learning expe [...] Read more

Open Access Journal Article
Machine Learning-Based Approaches for Image Captioning
by Daniel Harris
Abstract
The field of computer vision has witnessed significant advancements with the advent of machine learning techniques. Among these advancements, image captioning stands out as a challenging task that involves generating textual descriptions of images. This paper presents a comprehensive overview of machine learning-based approaches for image captioning. We discuss the evolution of [...] Read more

Open Access Journal Article
Enhancing Medical Image Classification with Transfer Learning Techniques
by Daniel Thomas
Abstract
The field of medical image classification is rapidly evolving, especially with the increasing availability of large-scale datasets and advanced machine learning models. This paper focuses on enhancing the performance of medical image classification by leveraging transfer learning techniques. Transfer learning is a machine learning approach that utilizes knowledge gained from on [...] Read more

Open Access Journal Article
Autonomous Learning Systems for Personalized Education Platforms
by John Harris
Abstract
This paper explores the potential of autonomous learning systems in revolutionizing personalized education platforms. With the rapid advancement of technology, there has been a growing need for individualized learning experiences that cater to the diverse needs and preferences of students. Autonomous learning systems, equipped with machine learning algorithms, provide a promisi [...] Read more

Open Access Journal Article
Deep Reinforcement Learning for Real-Time Strategy Games
by Sophia Anderson
Abstract
This paper explores the application of deep reinforcement learning (DRL) techniques in the field of real-time strategy (RTS) games. Real-time strategy games are complex, dynamic environments that require players to make rapid decisions under uncertainty. DRL has emerged as a powerful tool for training intelligent agents capable of learning optimal strategies through self-play. [...] Read more

Open Access Journal Article
Machine Learning Applications in Remote Sensing Data Analysis
by Michael Martin
Abstract
The rapid advancement of machine learning techniques has revolutionized various fields, including remote sensing data analysis. This paper explores the applications of machine learning in the analysis of remote sensing data, highlighting its potential to enhance the accuracy and efficiency of data interpretation. Remote sensing data, collected from satellites and aerial platfor [...] Read more

Open Access Journal Article
Machine Learning Models for Predicting Stock Price Movements
by James Brown
Abstract
This paper explores the application of machine learning models in predicting stock price movements within the financial markets. The study aims to investigate the effectiveness of various machine learning algorithms in forecasting stock prices, with a focus on accuracy, robustness, and adaptability. By analyzing historical stock price data, the research employs several machine [...] Read more

Open Access Journal Article
Integrating Blockchain Technology with Deep Learning for Secure Healthcare Data Sharing
by John Johnson
Abstract
The rapid advancement in the healthcare sector has led to an exponential increase in the volume of patient data, which necessitates secure and efficient sharing mechanisms. Blockchain technology, renowned for its inherent security features, and deep learning algorithms, capable of processing complex data patterns, present promising solutions to address these challenges. This pa [...] Read more

Open Access Journal Article
Adaptive Control Strategies in Autonomous Vehicles Using Reinforcement Learning
by James Martin
Abstract
The integration of autonomous vehicles into modern transportation systems demands sophisticated adaptive control strategies to ensure safety, efficiency, and reliability. This paper explores the application of reinforcement learning (RL) in developing such strategies for autonomous vehicles. We delve into how RL algorithms can be employed to optimize decision-making processes i [...] Read more

Open Access Journal Article
Explainable AI Models for Interpretable Machine Learning
by Emma White
Abstract
The field of artificial intelligence has witnessed significant advancements with the development of complex machine learning models. However, these models often operate as "black boxes," making their decision-making processes opaque to human understanding. This lack of transparency poses challenges in various domains, particularly where human trust and accountability are crucia [...] Read more

Open Access Journal Article
Autonomous Navigation of UAVs Using Deep Reinforcement Learning
by Michael Martin
Abstract
The field of Unmanned Aerial Vehicles (UAVs) has witnessed significant advancements in recent years, with autonomous navigation being one of the key areas of focus. This paper investigates the application of Deep Reinforcement Learning (DRL) techniques for achieving autonomous navigation capabilities in UAVs. Deep Reinforcement Learning integrates deep neural networks with rein [...] Read more

Open Access Journal Article
Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning
by David Anderson
Abstract
The integration of the Industrial Internet of Things (IIoT) has revolutionized the industrial sector by enabling the collection and analysis of vast amounts of data from various industrial processes. One of the key applications of this technology is predictive maintenance, which aims to minimize downtime and maximize the operational efficiency of industrial equipment through ea [...] Read more

Open Access Journal Article
Evolutionary Computation Techniques for Parameter Optimization in Machine Learning Models
by Emma White
Abstract
The increasing complexity of machine learning models has led to a critical need for effective parameter optimization techniques to achieve optimal performance. This paper explores the application of evolutionary computation techniques in parameter optimization for machine learning models. Evolutionary algorithms, such as Genetic Algorithms (GAs) and Particle Swarm Optimization [...] Read more

Open Access Journal Article
Deep Learning Models for Biometric Authentication Systems
by Olivia Thomas
Abstract
The rapid advancement in artificial intelligence and deep learning techniques has revolutionized the field of biometric authentication systems. This paper explores the integration of deep learning models in various biometric authentication methods, including facial recognition, fingerprint scanning, and iris recognition. The aim is to enhance the accuracy, speed, and robustness [...] Read more

Open Access Journal Article
A Novel Deep Learning Approach for Predicting Stock Market Trends
by Emily Johnson
Abstract
This paper presents a novel deep learning approach for predicting stock market trends, aiming to improve the accuracy and efficiency of stock market forecasting. Traditional financial models often suffer from high complexity and limited predictive performance, which has motivated the exploration of deep learning techniques in this domain. The proposed model utilizes a combinati [...] Read more

Open Access Journal Article
Deep Reinforcement Learning for Autonomous Decision-Making in Robotics
by John White
Abstract
This paper delves into the integration of deep reinforcement learning (DRL) techniques for autonomous decision-making in robotics. The advent of DRL has revolutionized the field by providing intelligent agents the ability to learn complex decision-making processes through interaction with their environment. The study explores how DRL algorithms, such as Deep Q-Networks (DQN) an [...] Read more

Open Access Journal Article
Context-Aware Recommendation Systems Using Machine Learning and User Behavior Analysis
by Michael Jackson
Abstract
This paper presents a comprehensive overview of the evolving field of context-aware recommendation systems (CARS), which integrate machine learning algorithms with user behavior analysis to enhance the personalization of recommendations. The study delves into the significance of understanding the context in which recommendations are made, as this context can significantly influ [...] Read more

Open Access Journal Article
Computational Intelligence Techniques for Environmental Monitoring and Management
by Emma White
Abstract
The rapid urbanization and industrialization have significantly altered the global environment, necessitating the implementation of effective environmental monitoring and management strategies. This paper explores the integration of computational intelligence techniques in addressing these environmental challenges. Computational intelligence encompasses various methodologies su [...] Read more