Search Results - (( model selection method algorithm ) OR ( based information resources algorithm ))

Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

“…Hence, this study aims to develop the dynamic configuration algorithm to provide an optimal support assignment based on information generated from both social support recipient and provision computational models. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…Next, the ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”

A review energy-efficient task scheduling algorithms in cloud computing by Atiewi S., Yussof S., Ezanee M., Almiani M.

Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Efficient Clustering Method by Hasan, Nurul

“…We introduce a modified cluster based model by using special nodes called server nodes (SN) that is powerful in term of resources. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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OFF-GRID SOLAR PHOTOVOLTAIC (PV) DESIGN BASED ON FUZZY TECHNIQUE FOR ORDER PERFORMANCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) APPROACH by NUR AFIQAH, JAHILAN

“…The aforementioned technique is the MCDM method, particularly the fuzzy TOPSIS algorithm. This algorithm is embedded in the PV system to select the best PV components’ configuration based on multiple criteria. …”
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Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

Prediction on weather forecast based on cloud shapes using CNN / Muhammad Ashraff Noor Azmi by Noor Azmi, Muhammad Ashraff

“…The development phase focuses on implementing the CNN algorithm specifically for weather prediction based on cloud shapes. …”
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Hybridflood algorithms minimizing redundant messages and maximizing efficiency of search in unstructured P2P networks by Barjini, Hassan

“…We proposed two novel search algorithms named QuickFlood and HybridFlood. QuickFlood combines two food-based searches; fooding and teeming. …”
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Modelling and control strategies for hydrokinetic energy harnessing by Wan Ismail, Ibrahim

“…Subsequently, the metaheuristic method based on the combination of the Hill-Climbing Search (HCS) MPPT algorithm and the Fuzzy Logic Controller has been proposed to produce a variable step size compared to the fixed step size in conventional HCS algorithm. …”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

“…There was not enough information available on the implementation of neural networks and genetic algorithm for the prediction and selecting input variables in oil palm yield and output energy. …”
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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

“…Firstly, the research methodically selects optimal predictor combinations from four distinct variable groups: Landsat-9 (L1) data, a fusion of Landsat-9 data and Vegetation-based indices (L2), and the integration of Landsat-9 data with the Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) (L3) and the combination of best predictors (L4) derived from L1, L2, and L3. …”
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A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces by A. Mostafa, Salama, Ravi, Sharran, Zebari, Dilovan Asaad, Zebari, Nechirvan Asaad, Mohammed, Mazin Abed, Nedoma, Jan, Martinek, Radek, Deveci, Muhammet, Ding, Weiping

“…Moreover, Cross-Stage Partial (CSP) DarkNet53 is used to improve the feature extraction and to facilitate the model’s object detection ability. A data augmentation algorithm is used for feature generation to enhance the model’s training robustness. …”
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Effectiveness of simple terminological ontology to support document retrieval in a specialized domain / Seyed Abolfazle Moosavifar by Moosavifar, Seyed Abolfazle

“…The research objectives are structured to introduce new algorithms for ontology-based automatic annotation, retrieval and ranking of documents and to check on the reliability of WordNet to provide lexical support for the (simple terminological) ontology-based document retrieval. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…The similarity between ambiguous words and their context words is evaluated using the cosine similarity approach. A rule-based method is introduced to select context words based on their similarity. …”
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Consumers' intention to use e-money mobile using the decomposed theory of planned behavior by Husnil, Khatimah

“…The Partial Least Squares Method (PLS) series PLS 2.0 M3 for algorithm and bootstrap techniques and SPSS 18 was used to test the hypothesis that has been developed. …”
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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq by Yaseen, Z.M., Jaafar, O., Deo, R.C., Kisi, O., Adamowski, J., Quilty, J., El-Shafie, A.

“…The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. …”
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