Search Results - (( intelligence ai protocol algorithm ) OR ( intelligence based svm algorithm ))

Intelligent DNA signature detection for internet worms by Ghazali, Osman

“…Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

“…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

“…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network by Rashid, Sami Abduljabbar, Audah, Lukman, Hamdi, Mustafa Maad, Jubair, Mohammed Ahmed, Hassan, Mustafa Hamid, Abood, Mohammed Salah, A. Mostafa, Salama

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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network by Sami Abduljabbar Rashid, Sami Abduljabbar Rashid, Lukman Audah, Lukman Audah, Mustafa Maad Hamdi, Mustafa Maad Hamdi, Mohammed Ahmed Jubair, Mohammed Ahmed Jubair, Mustafa Hamid Hassan, Mustafa Hamid Hassan, Mohammed Salah Abood, Mohammed Salah Abood, Salama A. Mostafa, Salama A. Mostafa

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Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Vanessa, Penshie, Hamada Rasheed Hassan, Al-Absi

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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

“…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

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Comparative performance of machine learning algorithms for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani

“…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. …”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

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A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients by Rahman, Md Saidur, Md Nor, Nor Saadah

“…The other way around, AI is a limb of Computer Science dedicated to developing systems that do what a human does intelligently. …”
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A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

“…This thesis presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm - Least Square Support Vector Machine (CS-LSSVM). …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

“…Objective: This study aims to predict the academic performance of dental students based on their admission results using Artificial Intelligence. …”
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Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…Due to the increased computational effort from HS-SVM and HS-RF, a modified HS (MHS) hybridized with SVM and RF are proposed in this study for an effective yet efficient search. …”
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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.] by M. A., Hambali, Y. K, Saheed, M. D, Gbolagade, M, Gaddafi

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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…Additionally, graphical analysis confirmed that the predictive accuracy of SVM model is superior, compared to other models. …”
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