Search Results - (( exploring e function algorithm ) OR ( java data selection algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Dhany, Saputra

“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database by Yusof, Mohd Kamir, Abdul Rahman, Mohd Nordin, Azlan, Atiqah

“…Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A Hamid, Rahayu

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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…Enhancements could also be done to eGSA by exploring the possibility to hybrid the algorithm with other well-known meta heuristic algorithms.…”
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Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

“…The performances of all modified ABC variants and formulated memetic ABC algorithms have been evaluated on 27 benchmark functions. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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A new multiobjective tiki-taka algorithm for optimization of assembly line balancing by M. F. F., Ab Rashid, Ariff Nijay, Ramli

“…Purpose: This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simultaneously. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…The numerical results obtained from the performance evaluation indicated that the RX crossover is the most fitting pair to the STPM mutator in competently solving two CS problems i.e. minimizing a molecular potential energy function and finding the most stable conformation of pseudoethane through a molecular model, which involves a realistic energy function.…”
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E-nose for basal stem rot detection by Ali Yeon, Md Shakaff, Prof. Dr., Mazlee Noor, Ahmad. Dr., Marni Azira, Markom, Abdul Hamid, Adom, Wahyu, Hidayat, Abu Hassan, Abdullah, N., Ahmad Fikri

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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
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Vibrant search mechanism for numerical optimization functions by Shambour, Moh’d Khaled Yousef

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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Nevertheless, many metaheuristic algorithms are still suffering from a low convergence rate because of the poor balance between exploration (i.e. roaming new potential search areas) and exploitation (i.e., exploiting the existing neighbors). …”
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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
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Irrigation management based on reservoir operation with an improved weed algorithm by Ehteram M., Singh V.P., Karami H., Hosseini K., Dianatikhah M., Hossain M.S., Fai C.M., El-Shafie A.