Search Results - (( developing solving means algorithm ) OR ( java implication tree algorithm ))

Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

“…Vertex support Algorithm (VSA). Mean of Neighbors of Minimum Degree Algorithm (MNMA), Modified Vertex Support Algorithm (MVSA), Maximum Adjacent Minimum Degree Algorithm (MAMA), and Clever Steady Strategy Algorithms (CSSA). …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

“…The objectives of this research are to develop an algorithm for integrated scheduling and conflict-free routing of jobs and AGVs in FMS environment using a hybrid genetic algorithm, ensure the algorithm validity and improvement on the performance of the developed algorithm. …”
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Faculty timetabling using genetic algorithm by Liong, Boon Yaun

“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The algorithm developed in this thesis contains three sub-algorithms. …”
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Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

“…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. …”
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Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

“…The complexity of combinatorial problems is classified as NP meaning that algorithms are yet to exist to efficiently solve the problem. …”
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Signal Noise Removal using Concurrent Algorithm by Hammuzamer Irwan , Hamzah, Azween, Abdullah

“…This research is in the early phase to solve the problem of how to develop a signal noise removal process using concurrent algorithm. …”
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Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

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Pemahaman guru matematik Tahun Enam tentang pembahagian nombor bulat / Hoi Sim Min by Hoi , Sim Min

“…Data was collected through five clinical interviews involving mental images, representations, meaning, reasoning and problem solving, which was captured on video. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays by Prajindra�Sankar K., Kiong T.S., Siaw�Paw J.K.

Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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Hybrid particle swarm optimization algorithm with fine tuning operators by Murthy, G.R., Arumugam, M.S., Loo, C.K.

“…This paper introduces a new approach called hybrid particle swarm optimization like algorithm (hybrid PSO) with fine tuning operators to solve optimisation problems. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem by Abdelraheem Elhaj, Hazir Farouk

“…This means that it is highly unlikely to find a polynomial algorithm to solve the problem. …”
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A COMPUTATIONAL ALGORITHM for the NUMERICAL SOLUTION of NONLINEAR FRACTIONAL INTEGRAL EQUATIONS by Amin, R., Senu, N., Hafeez, M.B., Arshad, N.I., Ahmadian, A.L.I., Salahshour, S., Sumelka, W.

“…For different number of collocation points (CPs), maximum absolute and mean square root errors are computed. The results show that for solving these equations, the HWCT is effective. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations by Nouri, Hossein, Tang, Sai Hong

“…This paper investigates the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem. In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

Stochastic optimal control of economic growth model under research and development investment with Kalman filtering approaches by Lim, Yue Yuin, Kek, Sie Long, Leong, Wah June

“…With these state estimates, two different computational algorithms are proposed, the EKF for state-control (EKF4SC) and UKF for state-control (UKF4SC) algorithms. …”
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