بدائل البحث:
learning algorithm » learning algorithms (توسيع البحث)
models algorithm » mould algorithm (توسيع البحث), deer algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
involves » involved (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
models algorithm » mould algorithm (توسيع البحث), deer algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
involves » involved (توسيع البحث)
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281
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
منشور في 2021"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"
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282
Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
منشور في 2020"…An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …"
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283
A novel hybrid methodology for fault diagnosis of wind energy conversion systems
منشور في 2023"…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …"
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284
A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation
منشور في 2024"…By thoroughly reviewing the existing literature and methodologies, this paper provides a comprehensive overview of the approaches used in ambulance allocation, routing, demand estimation and simulation models. We discuss the challenges faced by these methods, emphasizing the need for innovative solutions that can adapt to real-time data and changing emergency patterns. …"
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285
Framework for rapid design and optimisation of immersive battery cooling system
منشور في 2025"…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). …"
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286
Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
منشور في 2024"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"
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287
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
منشور في 2024"…In a postfault scenario, a copula of processing blocks is implemented to ensure the reliability of the proposed method where high-importance features are incorporated into the TCN-GWO model. The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"
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288
Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
منشور في 2025"…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…"
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289
Adaptive Video Streaming Over Cognitive Radio Networks
منشور في 2017احصل على النص الكامل
doctoralThesis -
290
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
منشور في 2019"…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …"
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291
Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements
منشور في 2020"…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. …"
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292
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293
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294
Structural similarity evaluation between XML documents and DTDs
منشور في 2007"…We consider the various DTD operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes. Our approach is based on the concept of tree edit distance, as an effective and efficient means for comparing tree structures, XML documents and DTDs being modeled as ordered labeled trees. …"
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conferenceObject -
295
A hybrid approach for XML similarity
منشور في 2007"…Various algorithms for comparing hierarchically structured data, e.g. …"
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conferenceObject -
296
Investigation of Forming a Framework to shortlist contractors in the tendering phase
منشور في 2022"…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …"
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297
Improving Rule Set Based Software Quality Prediction
منشور في 2003احصل على النص الكامل
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298
Phased Array Technique for Brain Source Localization
منشور في 2012احصل على النص الكامل
doctoralThesis -
299
STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
منشور في 2025"…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …"
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300
Cross entropy error function in neural networks
منشور في 2002"…To forecast gasoline consumption (GC), the ANN uses previous GC data and its determinants in a training data set. …"
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conferenceObject