Search Results - (( developing effective commitment algorithm ) OR ( java _ prediction algorithm ))

Mobile phone customers churn prediction by using Elman and Jordan recurrent neural network with reinforcement learning algorithm / Muhammad Syahir Mohd Ribuan by Mohd Ribuan, Muhammad Syahir

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Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

“…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…This thesis clarifies the issue using the objective method to develop the GA metric selection model for predicting the maintainability of object-oriented systems. …”
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MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

“…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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Effect of business social responsibility (BSR) on performance of SMEs in Nigeria by Gorondutse, Abdulahi Hassan

“…Therefore, significant positive effects of commitment, trust, and perceived ethics suggest that the variables are important in relation to performance. …”
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AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…Results from this study indicates the usage of k-NN is proven to be most effective algorithm in terms of performance and accuracy required by the shipping industry fraud detection.…”

Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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Examining leadership style and ethical reasoning in Nigeria public sector by Felix, Chikelu Okey

“…Findings also showed that the relationship between transformational leadership and post conventional cognitive moral development was found to be significantly moderated by religiosity commitment and vertical individualism and collectivism. …”
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Fair Traffic Scheduling and Shaping Algorithms for Diffserv Networks by Mohamed, Mohamed Awad Elshaikh

“…This thesis investigates the effect of different scheduling mechanisms and usage of a different marker algorithms then develop and implement a fair scheduling mechanism and integrate it with a shaper with the usage of a very fair efficient marker at the edge of the DiffServ networks with the usage of simulation and analytical techniques. …”
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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List by Othman M.N.C., Rahman T.K.A., Mokhlis H., Aman M.M.

“…This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). …”

Fraud Detection in Shipping Industry using K-NN Algorithm by Subramaniam G., Mahmoud M.A.

Optimal economic load dispatch using multiobjective cuckoo search algorithm by Yasin Z.M., Aziz N.F.A., Salim N.A., Wahab N.A., Rahmat N.A.

“…In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. …”

Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman by Che Othman, Muhammad Nazree

“…From the result obtained and the comparative study conducted, it is proved that the proposed MAEP-PL optimisation technique has able to solve the unit commitment problem where, the total daily generation cost is effectively minimised and the computation time is reduced as compared to other techniques.…”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

“…The second-level learner uses logistic regression (LR) to aggregate the final prediction output. The landslide data together with its conditioning factors (feature variables) collected from three districts in the Central Java Province, Indonesia, has been used as the case study for the LSM. …”