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EDRAAK
ISSN 3078-8412 · Peninsula Publishing Press · 37 artikel di indeks
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Artikel Jurnal
Machine Learning Enhanced Artificial Bee Colony for Solving Inverse Problems: Surrogate-Guided Reconstruction under Measurement Noise
Inverse problems are fundamental to a variety of scientific and engineering problems, but are commonly ill-posed, nonlinear, and sensitive to measurement errors. In this study, a novel machine learning based ABC framework (ML-ABC) is introduced to enhance the stability of and the efficiency in IP…
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Artikel Jurnal
Explainable AI for Healthcare: Training Healthcare Workers to Use Artificial Intelligence Techniques to Reduce Medical Negligence in Ghana’s Public Health Act, 2012 (Act 851)
This analysis examines whether Ghana’s Public Health Act, 2012 (Act 851) imposes adequate legal responsibilities on healthcare facilities concerning personnel training on artificial intelligence (AI) systems and implementation of medical negligence reduction measures. Through an evaluative review…
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Enhancing Point-of-Interest Recommendation Systems through Multi-Modal Data Integration in Location-Based Social Networks: Challenges and Future Directions
The rapid development of location-based networks (LBSNs) has transformed many aspects of tourism and management by changing the way travelers interact with destinations. However, changes in data analysis pose a major challenge to POI computational models, limiting their ability to generate…
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Artikel Jurnal
Seasonal Temperature Prediction in Niamey: A Prophet Model Approach
Precise seasonal temperature forecasting is basic for climate versatility agrarian planning and vitality administration in parched regions This study presents a data driven approach for foreseeing seasonal temperature trends in Niamey utilizing the Prophet model a vigorous timeseries forecasting…
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Artikel Jurnal
Using Random Forest Algorithm to Improve Investment Decision Making in Damascus Stock Exchange
This research aims to explore the potential of using the Random Forest algorithm to improve investment decision-making in the Damascus Stock Exchange. Google Trends data related to key economic indicators were analyzed to develop a predictive model capable of identifying potential investment…
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Artikel Jurnal
Deep Learning-Based Neural Network Modeling for Economic Performance Prediction: An Empirical Study on Iraq
This study investigates the application of deep learning-based neural networks for predicting Iraq’s economic performance. Traditional econometric models impose restrictive assumptions that limit their predictive accuracy, especially in volatile economic environments. To overcome these limitations…
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Artikel Jurnal
Economic Performance Classification in Iraq (2000–2023): A Statistical Analysis Using Machine Learning with Support Vector Machines and Random Forest
This research investigates the classification of Iraq's economic performance from 2000 to 2023 using machine learning methodologies, specifically Support Vector Machines (SVM) and Random Forest (RF). The study aims to leverage macroeconomic indicators to develop predictive models for economic state…
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Artikel Jurnal
Deep Learning-Based Time Series Forecasting: A Convolutional Neural Network Approach for Predicting Inflation Trends
This study investigates the application of Convolutional Neural Networks (CNNs) for forecasting inflation trends in Egypt, aiming to enhance the accuracy of economic predictions by capturing complex, non-linear temporal dependencies in time series data. Traditional econometric models, such as ARIMA…
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Application of Deep Learning and Transfer Learning Techniques for Medical Image Classification
The advancements in deep learning (DL) and transfer learning (TL) have transformed artificial intelligence, particularly in image classification. This research examines the theoretical foundations of DL and TL, focusing on their applications in medical image classification, specifically…
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Artikel Jurnal
Enhancing Economic Growth Time Series for UAE Forecasting with Deep Learning: A Seq2Seq and Attention-Driven LSTM Approach
This study aims to enhance economic growth forecasting in the United Arab Emirates (UAE) by implementing a Seq2Seq deep learning model with an attention-driven Long Short-Term Memory (LSTM) network. Traditional statistical models often fail to capture the complex temporal dependencies and nonlinear…
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Artikel Jurnal
Classification Arabic language (Classical Arabic Poetry, Al-Hur Arabic Poetry and Prose) Using Machine Learning
Many languages globally have made significant advances in electronically studying and classifying texts. Making electronic text a great alternative to manual classification by saving time, cost, and effort. However, Arabic has not seen similar progress due to several limitations faced by…
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Artikel Jurnal
Comparative Evaluation of Ensemble Learning Algorithms for Early Detection of Diabetes
Diabetes is a severe metabolic disorder that poses a significant worldwide health challenge. Early detection is crucial to avoid serious complications and reduce healthcare burdens. Despite the rising use of machine learning in medical diagnostics, many studies rely on single algorithms, which…
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Artikel Jurnal
Detecting Similarity License Plate Vehicle License Via Using Deep CNNs in Complex Surroundings
As our society has developed, cars on the road have increased. Manual license plate recognition is challenging since it is significantly slower in real-time than when performed by a machine. The bulk of license plate recognition systems utilized morphological image processing until recently. The…
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Most Cited AI Research (2024–2025): A Cross-Sector Review
The blistering pace of generative and foundational AI models being deployed in 2024 and 2025 is transforming experiences in education, healthcare, science, sustainability and business. This narrative review consolidates findings from the 50 most cited peer reviewed publications in this time frame…
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Applications of Geospatial AI in Human Geography and Spatial Networks: A Literature Review
GeoAI is the internationally recognized term that describes the powerful nexus of artificial intelligence, spatial science, and big data analytics presents new and innovative avenues for understanding and addressing the challenges and opportunities faced by human societies at a geographic scale…
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Developing an Efficient Deep Learning Model for the Classification of Skin Lesions
This paper proposes a deep learning technique for classifying dermoscopic skin lesion pictures, improving diagnostic precision and clinical decision-making. The model extracts features using ResNet101V2 and infers using Monte Carlo dropout to determine prediction certainty. Grad-CAM additionally…
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Deep Learning-Driven Disease Prediction System in Cloud Environments using a Big Data Approach
Disease detection has gained great significance in the big data cloud systems as health organizations try to accrue manifold benefits from massive amounts of data to achieve better outcomes in patients. The ability to detect diseases with better efficiency can achieve timely interventions, better…
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Artikel Jurnal
Advancing Translation Quality Assessment: Integrating AI Models for Real-time Feedback
With the use of AI models for real-time reception a feedback, this review attempts to show how the assessment of the quality of translation is changing. The investigation covers aspects such as the technical side of the integration, efficiency and minimization of human errors, influence upon the…
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The Era of AI: The Impact of Artificial Intelligence (AI) and Machine Learning (ML) on Financial Stability in the Banking Sector
The impact of artificial intelligence and machine learning on financial stability: a socio-legal analysis of the banking sector. The purpose of the present analysis is to identify the impact of artificial intelligence and machine learning on financial stability in the banking sector. The…
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Artikel Jurnal
Fortifying AI Against Cyber Threats Advancing Resilient Systems to Combat Adversarial Attacks
The emerging complexity of the threats which the safer world faces as of now, let alone the adversary attacks, presents great troubles to the orthodox systems of cybersecurity. This research focuses on the use of AI to design and develop robust systems that prevent such shifting threats. As a…