Search Results - (( carlo simulation optimization algorithm ) OR ( motion evaluation path algorithm ))

Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables by ALAhmad A.K., Verayiah R., Ramasamy A., Marsadek M., Shareef H.

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Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

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Optimal sizing of hybrid tidal, photovoltaic and battery sources of energy by Sadeghi, Omid Sarrafan

“…The numbers of solar arrays, tidal turbines and battery were considered as optimization variables which have been determined by the particle swarm optimization algorithm. …”
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Mobile robot navigation using GPS to solve target location achieving problem / Saiful Zaimy Yahaya, Rozan Boudville and Mohamad Faizal Abdul Rahman by Yahaya, Saiful Zaimy, Boudville, Rozan, Abdul Rahman, Mohamad Faizal

“…The path finding algorithm will basically finds the best path and instructs the robot to moves to its location by keep on refreshing its positions. …”
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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

“…Additionally, the efficiency of the planned algorithm in numerical simulation was compared to that of the "Monte Carlo simulation" (MCS).…”
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A Fuzzy Logic Positional-Based Controller For Sensorbased Robotic Motion Planning by Khaksar W., Yousefi M., Saharia K.S.M., Ismail F.B.

“…Despite the large volume of research in this field, the computational complexity of the motion planning and the increasing potential application domains require more accurate and efficient motion planning algorithms. …”

A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”

Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar, Weria, Tang, Sai Hong, Mohamed Sahari, Khairul Salleh, Khaksar, Mansoor, Toressen, Jim

“…The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. …”
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Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M., Torresen J.

Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Optimization of RFID network planning using MDB-FA method by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

“…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the scanning tasks need to be segregated and assigned for each scanner head, and path planning where the best combinatorial paths for each scanner are determined in order to minimize the total motion of scanning time. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

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Inventory optimization using simulation approach / Nuridawati Baharom and Pa’ezah Hamzah by Baharom, Nuridawati, Hamzah, Pa’ezah

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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”

Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”

Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…This would allow the FLC to generate a local path for an obstacle avoidance system unique to mobile robot navigation in dynamic environments. …”
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