بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
update » updated (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
update » updated (توسيع البحث)
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161
Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
منشور في 2022"…The values are 18.44 % and 23.9 % for CV-RMSE, 11.6 % and 10.06 % for MAPE, and 7.5 % and 6.75 % for MdAPE, using ANN and GP, respectively. While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…"
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162
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163
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164
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
منشور في 2020"…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …"
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165
Correlation Clustering with Overlaps
منشور في 2020احصل على النص الكامل
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masterThesis -
166
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167
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168
Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
منشور في 2019"…The flags pertaining to 16x16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. …"
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article -
169
Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
منشور في 2020"…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. …"
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170
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
منشور في 2022"…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …"
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masterThesis -
171
Sentiment visualization of correlation of loneliness mapped through social intelligence analysis
منشور في 2024"…By using natural language (NLP) processing, sentiment analysis, and topic modeling, we seek to understand prevalent sentiments and concerns. …"
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172
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
منشور في 2021احصل على النص الكامل
doctoralThesis -
173
Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
منشور في 2023"…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …"
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174
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175
Software defect prediction. (c2019)
منشور في 2019احصل على النص الكامل
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masterThesis -
176
Deploying model obfuscation: towards the privacy of decision-making models on shared platforms
منشور في 2024"…The implementation nuances involve data and model sharing among allies and partners working on the same domain. …"
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177
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178
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179
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180