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221 results for “hybrid model”
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Research ArticleOpen accessEvery word in the titleA Hybrid Artificial Neural Network Model for Option PricingHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiIn the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Aug 2019 · 7,410 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA HYBRID INTELLIGENT MODEL FOR SOFTWARE COST ESTIMATIONWei Lin Du, Luiz Fernando Capretz, Ali Bou Nassif, Danny HoAccurate software development effort estimation is critical to the success of software projects. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in handling uncertain and imprecise inputs and collinear characteristics. In this study, a hybrid intelligent model combining … …Journal of Computer Science, Vol. 9, Issue 11 · 28 Sep 2013 · 7,745 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Traffic Management Model for Multi-Protocol Label Switching NetworkE. R. Naganathan, S. RajagopalanProblem statement: MPLS is a highly scalable, protocol agnostic and data-carrying mechanism. Traffic engineering is the major research area in MPLS due to the emerging requirements of MPLS and the internet usage. A major objective of traffic engineering is to minimize or eliminate high-loss situations. Another goal of traffic engineering is to balance the Quality of Service (QoS) against the … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 15 Oct 2011 · 7,094 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Approach based on Winter's Model and Weighted Fuzzy Time Series for Forecasting Trend and Seasonal DataSuhartono, Muhammad Hisyam LeeProblem statement: In the literature, the most studied of fuzzy time series for the purpose of forecasting is the first order fuzzy time series model. In this model, only the first lagged variable is used when constructing the first order fuzzy time series model. Therefore, such approaches fail to analyze accurately trend and seasonal time series which is an important … …Journal of Mathematics and Statistics, Vol. 7, Issue 3 · 18 Jul 2011 · 7,942 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMorphological Database and Quantification of Liberica Coffee Beans Using a Hybrid CNN ModelDioneces O. Alimoren, Francis G. Balazon, Jonnah R. Melo et al.Traditional evaluation of Liberica coffee (Kapeng Barako) in Batangas is commonly performed through manual visual inspection and sensory judgment, which are slow, subjective, and difficult to reproduce across farms, buyers, and grading personnel. These limitations can lead to inconsistent quality classification, weak traceability, and reduced bargaining power for local producers. This study develops and validates a web-based morphological analysis system … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,337 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Deep Learning Model for Evaluating Subjective Answers Based on Semantic Textual SimilaritySiddhesh Kudtarkar, Kavita ShirsatSubjective answer evaluation requires accurately identifying semantic similarities between student and reference responses. This study introduces a Hybrid Deep Learning Model (HDLM) that integrates CNN, GRU, and LSTM architectures to assess Semantic Textual Similarity (STS) more effectively. The HDLM employs two parallel branches-CNN-GRU and CNN-LSTM to capture both local syntactic features and long-range contextual dependencies, followed by Manhattan distance for … …Journal of Computer Science, Vol. 22, Issue 4 · 7 Apr 2026 · 1,690 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,897 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,048 accessesView PDFCite