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Titlebook: Innovations in Smart Cities Applications Volume 7; The Proceedings of t Mohamed Ben Ahmed,Anouar Abdelhakim Boudhir,İsmail Conference proce

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Water Amount Prediction for Smart Irrigation Based on Machine Learning Techniqueswithout wastage. In this paper, we proposed a smart irrigation solution using different Machine Learning (ML) models to predict the daily irrigation water amount for the cucumber crop. The various used ML takes the plant’s environmental conditions parameters as input to predict the suitable amount o
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Smart Irrigation System Using Low Energyention. The development of new intelligent systems in the field of agriculture has strengthened agricultural production, made it an altarpiece and reduced the cost of production. The purpose of this article is to realize a new fully autonomous model capable of functioning correctly in the agricultur
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Advancing Crop Recommendation Systems Through Ensemble Learning Techniquesp recommendation that leverages machine learning techniques, specifically ensemble learning with a voting classifier. A comprehensive analysis of prior research in the field of crop recommendation systems reveals the limitations and challenges of previous approaches, particularly their low accuracy.
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Technology to Build Architecture: Application of Adaptive Facade on a New Multifunctional Arena behaviour of indoor environment and the global comfort of a building are strictly dependent on the façade: traditional façades behave statically towards external and internal climate conditions. The objective of this study is to design an adaptive facade system with different layer functions, ensur
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A Comparative Analysis of Memory-Based and Model-Based Collaborative Filtering on Recommender Systemapplications adopting this model pushes companies to develop differentiation strategies. One of the strategies is to use emerging technologies to offer a better customer experience. Recommender systems (RSs) are AI-based solutions that can provide customized recommendations. To implement an RS in a
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Critical Overview of Model Driven Engineeringtrong focus on using models to represent the various facets of a software system. These models serve as the foundation for creating executable code. Even though MDE has proved effective in some situations, there are still difficulties with the method, such as the difficulty of modeling specific syst
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A Synthesis on Machine Learning for Credit Scoring: A Technical Guideselection of an appropriate algorithm to be used in a particular application can be challenging due to the complexity of the various techniques that are available as well as the high cost of implementing and debugging sophisticated models. In this paper, we examine the use of multiple machine learni
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Enhancing Writer Identification with Local Gradient Histogram Analysison, and historical research. In this article, we propose a novel approach for writer identification using gradient angle histograms collected from neighboring pixels. By calculating the histogram of gradient angles from different locations of neighboring pixels, we effectively capture the writer’s u
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