Search Results - (( sequence optimization window algorithm ) OR ( sequence optimisation system algorithm ))

Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Future work may consider introducing more features to the system, applying them to other languages, and integrating it with sequence learning for more accuracy.…”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

“…In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm by Abubakar, Adamu, Chiroma, Haruna, Khan, Abdullah, Mohamed, Elbaraa Eldaw Elnour

“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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An Ant Colony System for Solving DNA Sequence Design Problem in DNA Computing by Farhaana, Yakop, Zuwairie, Ibrahim, Amar Faiz, Zainal Abidin, Zulkifli, Md. Yusof, Mohd Saberi, Mohamad, Khairunizam, Wan, Watada, Junzo

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NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali by Hambali, Najidah

“…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation by Mohd Zaidi, Mohd Tumari, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Faradila, Naim, Mohd Falfazli, Mat Jusof, Ismail, Ibrahim, Zulkifli, Md. Yusof, Kamal, Khalil, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi

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A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system by Tang, Sai Hong, Nouri, Hossein, Motlagh, Omid Reza Esmaeili

“…In addition, a newly-developed BFA-based optimisation algorithm has been compared with the branch and bound algorithm. …”
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A robust algorithm for solving nonlinear system of equations using trust-region and line-search techniques by Kabir, M. Nomani

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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

“…A non-parametric modelling approach of the system was proposed based on feed-forward neural networks (FNNs) while its weight and bias parameters were optimised using chaotic-enhanced stochastic fractal search (SFS) algorithm. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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ExploreEasy: Smart and all-in-one trip management application by Yap, Pei Nee

“…To improve travel efficiency, the system incorporates intelligent route optimisation using the Travelling Salesman Problem (TSP), ensuring time-efficient and logically sequenced itineraries. …”
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

“…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. …”
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A headway and order scheme based mixed integer goal programming model for railway rescheduling / Zuraida Alwadood by Alwadood, Zuraida

“…The approach considers the headway restriction and the sequence order of conflicting trains as its main feature. …”
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