Search Results - (( java implications _ algorithm ) OR ( parameter optimization strategical algorithm ))

Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”

Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions by Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.

“…Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. …”

Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm by Priyadi, Irnanda, Daratha, Novalio, Gunawan, Teddy Surya, Ramli, Kalamullah, Jalistio, Febrian, Mokhlis, Hazlie

“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

“…In addition, a certain number of nodes work as a temporary BS by aggregating the data packets from affiliated sensors via multi-hop. Furthermore, strategically divisioning the area of data collection, the optimization of the mobile element can be elevated. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…Thereafter, the Multi-Leader Particle Swarm Optimization algorithm (MLPSO), which is a novel evolutionary optimization technique in the field of power systems was developed and employed in the optimization process. …”

Particle swarm optimization in multi-user orthogonal frequency-division multiplexing systems by Lye, Scott Carr Ken

“…To minimize the power consumption, Particle Swarm Optimization (PSO) is utilized to find the exact or near optimal resource allocation for the users. …”
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A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun by Harun, Hasrul Hisyam

“…Antenna design in this paper simulated using Computer Simulation Technique (CST) and introduced Parameter Sweep and Genetic Algorithm (GA) technique to determine the optimal lengths of antenna and stubs. …”
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Efficient relay placement algorithm using landscape aware routing (erpalar) by Onabajo, Olawale Olusegun

“…ERP ALAR was implemented in Matlab R2009a using Genetic Algorithm (GA) with multi-objectives. GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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An economic order quantity model with completely backordering and nondecreasing demand under two-level trade credit by Molamohamadi, Zohreh, Arshizadeh, Rahman, Napsiah, Ismail, Amir, Azizi

“…The replenishment decisions optimally are obtained using genetic algorithm. Two special cases of the proposed model are discussed and the impacts of parameters on the decision variables are finally investigated. …”
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Distributed power control and beamforming for cognitive two-way relay networks using a game-theoretic approach by Iranpanah, Havzhin, Mohd Ali, Borhanuddin, Hashim, Fazirulhisyam, Mohamad, Hafizal

“…We propose a distributed power control and beamforming algorithm that enables the users operating in the underlay mode to strategically adapt their power levels, and maximize their own utilities subject to the primary user (PU) interference constraint, as well as its own resource and target signal-to-interference-and-noise-ratio (SINR) constraints. …”
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Traffic management algorithms for LEO satellite networks by Huyop @ Ayop, Fahrul Hakim

“…Those two algorithms are combined together due to the strong possibilities of being unable to achieve the optimal results when implemented separately. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Development of switchable planar reflectors for beam shaping realization by Abbasi, Muhammad Inam

“…Performance characterization for bandwidth and reflection loss optimization of different slot embedded patch configurations was done based on the scattering parameter measurements. …”
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Dynamic linear programming model for quarterly budget allocation and execution / Rossidah Wan Abdul Aziz by Wan Abdul Aziz, Rossidah

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Prioritisation assessment and robust predictive model for a comprehensive medical equipment maintenance using machine learning techniques / Aizat Hilmi Zamzam by Aizat Hilmi, Zamzam

“…The development of predictive models for objectives 1 and 2 of this study involves the application of seven supervised machine learning algorithms. The effectiveness of these models is assessed through eleven performance evaluation parameters. …”
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