Search Results - (( parameter optimization based algorithm ) OR ( using active problem algorithm ))

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm by Khan, Abdullah, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Voltage constrained optimal power flow based using genetic algorithm by Yassir Asnawi, Teuku Hasannuddin

“…In this study, Genetic Algorithm (GA) was applied to solve the problem of OPF. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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Firefly Algorithm based LCL filtered grid-tied STATCOM design for reactive power compensation in SCIG based Micro-grid by Saxena N.K., Gupta A.R., Mekhilef S., Gao W.D., Kumar A., Gupta V., Netto R.S., Kanungo A.

Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Two publicly activity datasets are used; Wireless Sensor Data Mining (WISDM) and Physical Activity Monitoring for Aging People (PAMAP2). …”
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Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

“…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”

New synchronization protocol for distributed system with TCP extension by Bayat, Peyman

“…The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
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Forecasting of fine particulate matter based on LSTM and optimization algorithm by Zaini N., Ahmed A.N., Ean L.W., Chow M.F., Malek M.A.

“…Long short-term memory based on metaheuristic algorithms, namely particle swarm optimization and sparrow search algorithm (PSO-LSTM and SSA-LSTM), are first developed and applied to determine the significance input combination to the changes of PM2.5 concentration at respective target stations. …”

The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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Stock indicator scanner customization tool using deep reinforcement learning by Cheong, Desmond YongHong

“…Moreover, ADAM optimization technique will be applied to adjust the parameters of the network in the DQN and ReLU activation function will be used since these techniques have shown promising achievement in some literature reviews. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
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Acltshe-Amts: A New Adaptive Brain Tumour Enhancement And Segmentation Approaches by Alkhafaji, Ali Fawzi Mohammed Ali

“…The AMTS approach segments and extracts the whole tumor, core tumor, and enhanced tumor regions from the brain MR images, integrating the Multi-Objective Grasshopper Optimization algorithm, Kapur Entropy, Cross-Entropy, and Localized active contour.…”
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PID Control Tuning Using PSO For Prosthetic Hand System by Rozaimi, Ghazali

“…Hand is one of the part human bodies with highest complex structures to control the movement involving a lot of numbers nerve endings connected.Amputees are disable person who has difficulties when dealing with their routine life activities because of physical problem such as lost all or part of an arm,hand or leg.The hand,the nerve endings are required high capabilities to control the velocity, positioning,force and movement of fingers.The main problems related to the prosthetic device are its functionality,lack of intuitive control and insufficient feedback due to lack of robust capability during ongoing operation.The primary purpose for this project is to focus on designing the prosthetic hand consist of controller based on Proportional Integral Derivative (PID) and Particle Swarm Optimization (PSO) control algorithms for patients with wrist and arm amputees.PSO is an optimization technique,inspired by social behavior of bird flocking or fish schooling.It can be used to tune the PID control parameters in order to achieve the desired performance target.Thus,the control technique for prosthetic hand positioning control by using PID controller that is tuned by PSO will be described thoroughly in this paper.The result is proved through simulation and in experiment,thus verifying the research hypothesis.…”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…The optimal schedules obtained were compared with the actual based on parameters and judgement from power plant planning team. …”

Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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Improving neural networks training using experiment design approach by Chong, Wei Kean

“…Conventionally, the parameters of a neural network are tuned by minimizing an objective function based on a pre-determined set of training data. …”
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