A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models حسب Azar, Danielle

"…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…"
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A synchronous/asynchronous multi-master replication method. (c2007) حسب Chahine, Amer Mohammad Kheir

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A Prioritized Uplink Call Admission Control Algorithm for 3G WCDMA Cellular Systems with Multi-Services حسب Al-Qahtani, Salman

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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology حسب Senyuk, Mihail

"…This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. …"
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Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges حسب Haseeb Javed (18576340)

الموضوعات:

Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب Ali Jassim Lari (22597940)

"…The data forecasting horizon used was a 24-h window in steps of 30 min. …"

Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms حسب Almahmood, Mothanna

"…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …"
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures حسب Leduc, Guillaume

"…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …"
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A data envelopment analysis model for opinion leaders’ identification in social networks حسب Hamed Baziyad (19273738)

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review حسب Mohamed Massaoudi (16888710)

"…With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performance and high PV forecastability potential compared to classical models. …"

A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) حسب Korkmaz, Rita

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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study حسب Alkhodari, Mohanad Ahmed

"…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …"
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Auto-indexing Arabic texts based on association rule data mining. (c2015) حسب Rouba G. Nasrallah

"…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …"
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GenDE: A CRF-Based Data Extractor حسب Kayed, Mohammed

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

الموضوعات:

Intelligent Fusion of Deep Features for Improved Waste Classification حسب Kashif Ahmad (12592762)

الموضوعات:

An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems حسب Boukhari, Bahia

"…Finally, the experimental results prove the improvements provided by our hash based algorithm over previously suggested models.…"
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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm? حسب Saravanan Thirumuruganathan (11038038)

"…The resulting model achieves an 89% predictive accuracy using historical data. …"

Deploying model obfuscation: towards the privacy of decision-making models on shared platforms حسب Sadhukhan, Payel

"…The implementation nuances involve data and model sharing among allies and partners working on the same domain. …"
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach حسب BILQUISE, GHAZALA

"…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …"
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