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17 results for “Multilayer Perceptron Network”
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Research ArticleOpen accessEvery word in the titleCross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural NetworksShirin A. Mojarad, Satnam S. Dlay, Wai L. Woo, Gajanan V. SherbetProblem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 20 Feb 2012 · 7,699 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCooling Load Prediction in the Under-Actuated Zone with Multilayer Perceptron Artificial Neural NetworkYaddarabullah, Aedah Abd Rahman, Amna SaadThis study focuses on addressing the challenge of predicting cooling loads in under-actuated zones, where the variability in occupant behavior, environmental conditions, and electronic usage creates complex dynamics. Traditional models like Support Vector Regression (SVR) and E-Lastic-Net (ELN) often struggle to capture these non-linear relationships, leading to inefficient Heating, Ventilation, and Air Conditioning (HVAC) management and increased energy consumption. To … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 5,300 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleData Optimization with Multilayer Perceptron Neural Network and Using New Pattern in Decision Tree ComparativelyMurat Kayri, Omay CoklukProblem statement: The aim of the present study is to exemplify the use of Artificial Neural Networks (ANN) for parameter prediction. Missing value or unreal approach to some questions in scale is a problem for unbiased findings. To learn a real pattern with ANN provides robust and unbiased parameter estimation. Approach: To this end, data was collected from 906 students … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,200 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite
Research ArticleOpen accessIn the keywordsArabic Sentiment Classification using MLP Network Hybrid with Naive Bayes AlgorithmMohammad Subhi Al-Batah, Shakir Mrayyen, Malek AlzaqebahSentiment analysis has recently become one of the growing areas of research related to text mining and natural language processing. Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. Most of the current studies related to this topic focus mainly on English … …Journal of Computer Science, Vol. 14, Issue 8 · 7 Aug 2018 · 9,273 accessesView PDFCite
Research ArticleOpen accessIn the keywordsElectrical Load Forecasting Using Artificial Neural Network: The Case Study of the Grid Inter-Connected Network of Benin Electricity Community (CEB)Adekunlé Akim Salami, Ayité Sénah Akoda Ajavon, Koffi A. Dotche, Koffi-Sa BedjaThe low rate of electrification seems challenging in many West African countries and many strategies are underway to improve upon. In this regard, the target of achieving the universal access and services calls for a stable and reliable electrical network. Forecasting of electrical load on a connected grid network is very delicate and requires tremendous task from the utilities (billing … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 11 Apr 2018 · 9,143 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDigital Hardware Implementation of a Neural System Used for Nonlinear Adaptive PredictionHassène Faiedh, Chokri Souani, Kholdoun Torki, Kamel BesbesNeural networks have been widely used for many applications in digital communications. They are able to give solutions to complex problems due to their nonlinear processing and their learning and generalization. Neural networks are one of the key technologies for the communication domain and accordingly a special effort may be expected to be paid to real time hardware implementation issues. … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 6,763 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCorrelation Based ADALINE Neural Network for Commodity TradingJ. Chandra, M. Nachamai, Anitha S. PillaiCommodity trading is one of the most popular resources owning to its eminent predictable return on investment to earn money through trading. The trading includes all kinds of commodities like agricultural goods such as wheat, coffee, cocoa etc. and hard products like gold, rubber, crude oils etc.,. The investment decision can be made very easily with the help of the … …Journal of Computer Science, Vol. 11, Issue 7 · 29 Oct 2015 · 7,825 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite