Search Results - (( weight distribution _ algorithm ) OR ( parameters estimation drop algorithm ))
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation
Published 2020“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm
Published 2006“…Finally, in the last method fuzzy reasoning is used for network congestion estimation and estimating time to start dropping incoming packets. …”
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Affine projection algorithm for speech enhancement using controlled projection order
Published 2020“…Then the corrupted signal is processed in a noise cancellation setup in such a way that three parameters of algorithm are changed according to the nature of the noise. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…To address this problem, an investigation was conducted on the ordered weighted model of the FCOM algorithm leading to proposed enhancements by introducing the beta distribution weighted fuzzy C-ordered-means clustering (BDFCOM). …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Moreover, the empirical results obtained showed that incorporating the AHP into Firefly Algorithm improved the accuracy of weight calculations in the multi-objective formulation of the optimisation process. …”
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability
Published 2024“…Therefore, this thesis proposes a new systematic Satisfiability logical rule namely Weighted Systematic 2 Satisfiability that uses a weighted feature to control the distribution of the negative literals. …”
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A binary archimedes optimization algorithm and weighted sum method for UFLS in islanded distribution systems considering the stability index and load priority
Published 2023“…This study proposes an under-frequency load-shedding (UFLS) scheme based on a binary Archimedes Optimization Algorithm (BAOA) and the Weighted Sum Method (WSM) to maintain the stability of an islanded distribution system. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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Peak pressure analysis of foot plantar distribution based on image processing algorithm
Published 2018“…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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Design and development of prototype robot gripper for object weight measurement
Published 2014“…Therefore, this study has proposed a robotic gripper prototype with a new configuration of pressure sensor distribution, based on development of grasping algorithm for object’s weight measurement. …”
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Implementasi Algoritma Cheapest Insertion Heuristic (CIH) dalam Penyelesaian Travelling Salesman Problem (TSP)
Published 2018“…The purpose of TSP is to find the route of all cities with minimum total weight.Many algorithms have been found to solve the TSP, one of which is the Cheapest Insertion Heuristic (CIH) algorithm in the process of inserting weighted steps obtained from the equation c (i, k, j) = d (i, k) + d (k, j) - d (i, j). …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Selection of access network using cost function method in heterogeneous wireless network
Published 2014“…This method covers the weight distribution and cost factor techniques.The weight distribution is used to measure different weights for existing wireless network based on the user's preference and mobile terminal power.The cost factor technique is also used to identify the cost for performing handover target by considering every network parameters and its weight.Results obtained showed that the algorithm has the ability to increase user's satisfaction compared to other algorithms, which consistently choose one accessible network.…”
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RWP-NSGA II: reinforcement weighted probabilistic NSGA II for workload allocation in fog and internet of things environment
Published 2024“…This paper proposes an improved version of NSGA II, namely, reinforcement weighted probabilistic NSGA II, which uses weighted probabilistic mutation. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
Published 2019“…This research aimed to reduce total power losses and improve voltage profiles of the distribution system by proposing a practical swarm optimizion algorithm GA genetic algorithm to optimize DG size and location by taking into consideration increase number of DG units in the system. …”
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Development of predictive modeling and deep learning classification of taxi trip tolls
Published 2022“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS
Published 2023“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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