Search Results - (( interval optimization techniques algorithm ) OR ( java implication based algorithm ))

Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique by Saliman, Nur Farah Ain

“…The optimizing of optimal path trace back system for Smith-Waterman algorithm using structural modelling techniques are presented in this paper. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. …”
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Machine failure prediction technique using recurrent neural network long short-term memory-particle swarm optimization algorithm by Rashid, N.A., Abdul Aziz, I., Hasan, M.H.B.

“…This paper proposes a hybrid prediction technique based on Recurrent Neural Network Long-Short-Term Memory (RNN-LSTM) with the integration of Particle Swarm Optimization (PSO) algorithm to estimate the Remaining Useful Life (RUL) of machines. …”
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Ant colony optimization in dynamic environments by Chen, Fei Huang

“…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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The optimization of solar drying of grain by using a genetic algorithm by Rahman, M.M., Mustayen, A.G.M.B., Mekhilef, Saad, Saidur, R.

“…Particularly in the low drying temperature drying is an energy intensive process and requires a suitable optimization technique. This work represents the kinetic simulation and energy efficient optimization technique for drying long grain, i.e. rice. …”
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Improving the efficiency of thermoelectric generator using perturb and observe MPPT algorithm by Nurul Izzah Izzati Zaihan, Tengku Norliza Tengku Mohamad, Fakroul Ridzuan Hashim

“…This paper proposes a design that integrates TEG arrays, boost converters, and the P&O algorithm to optimize power extraction from TEG systems. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control by Muhammad Firdaus, Masrom

“…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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An improvement of BFGS by applying n-th section method for solving unconstrained optimization / Nurul Atikah Mohamed Ramli by Mohamed Ramli, Nurul Atikah

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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

“…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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New Parameter Reduction of Soft Sets by Ma, Xiuqin

“…The related heuristic algorithms are given. In order to show the high efficiency of the proposed four algorithms, comparisons and analysis for decision making between OCCPR, IRDCCPR, ASPR, SPR and directly Interval-Valued Fuzzy Soft Sets based Fuzzy Decision Making algorithm (IVFSS-FDM) with three real-life datasets and ten synthetic generated datasets are made. …”
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Optimal search algorithm in a big database using interpolation–extrapolation method by Kabir, M. Nomani, Alginahi, Yasser M., Ali, J., Abdel-Raheem, E.

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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus by Megat Yunus, Puteri Nor Ashikin

“…After that, a hybrid of MLFNN with other optimization methods was introduced, i.e. Improved Fast Evolutionary Programming (IFEP), Evolutionary Programming- Dolphin Echolocation Algorithm (EPDEA) and Evolutionary Programming-Firefly Algorithm (EPFA). …”
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Solving unit commitment problem by using particle swarm optimization technique / Muhammad Aqil Ab Rahman by Ab Rahman, Muhammad Aqil

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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…Conventional computational optimal control techniques are designed for problems in which the control takes values in a connected set, such as an interval, and thus they cannot solve the problem directly. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”

Battery management optimization and lifecycle impact analysis for microgrid operation with V2G implementation / Muhammad Sufyan by Muhammad , Sufyan

“…The efficacy of the optimization algorithm is compared with other metaheuristic techniques for economic and reliability indices such as cost of electricity and loss of power supply probability. …”
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Existence and uniqueness for the evolutionary impulse control problem using an asynchronous algorithms by Haiour M., Bencheikh Le Hocine M.E.A., Jan R., Himadan A., Boulaaras S.

“…Our approach unfolds through a four-step methodology, leveraging distinctive features of a discrete iterative technique. This methodology integrates semi-implicit techniques with respect to the variable t and employs spatial approximation via finite element methods. …”