Search Results - (( developing function machine algorithm ) OR ( learning orientation optimization algorithm ))

Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…GA assists in optimizing the search process and performs machine learning. …”

Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

“…Fuzzy logic; Induction motors; Learning algorithms; Mean square error; Membership functions; Optimization; Particle swarm optimization (PSO); Rotors; Speed; Speed control; Stators; Torque; Transient analysis; Vector control (Electric machinery); Voltage control; Water craft; Backtracking search algorithms; Fuzzy membership function; Gravitational search algorithm (GSA); Indirect field oriented control; PI Controller; QLSA; Speed controller; Three phase induction motor; Controllers…”

Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

“…To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. …”
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Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptation algorithm. by Xiaohua, Qian, Neilson Ilan, Mersat, Haslina, Hashim, Bemen Wong, Win Keong

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Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…Besides this, CPU time for PSO was very high compared to other algorithms. In the future, other optimization algorithms will be tested for the CHFS model, such as Teaching Learning Based Optimization (TLBO) and the Crayfish Optimization Algorithm (COA).…”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Open architecture pc-based CNC controller by Yusoff, Wan Azhar

“…The objectives of this project are two: developing CNC controller and developing a prototype machine to implement the controller. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

“…A fitness function of production time incorporated of roughing and finishing process has been developed in Matlab Software. …”
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Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK by SINGH, NIHARIKA

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To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

“…EDM is one of the most accurate manufacturing processes for creating geometric shapes whether complex or simple in parts and assemblies. Development of EDM process has resulted in significant improvements in operating techniques, productivity and accuracy, which the result of this machining development has helped variability in EDM process. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The inertial sensor data was collected from the smartphone at two different positions and two different orientations. The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”

Smart Microgrid QoS and Network Reliability Performance Improvement using Reinforcement Learning by Singh, N., Elamvazuthi, I., Nallagownden, P., Badruddin, N., Ousta, F., Jangra, A.

“…The results validate the productivity and learning capabilities of the proposed QRL-MABR algorithm. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

“…The use of rule-based reasoning and genetic algorithms will optimize the case search and case adaptation process. �2008 IEEE.…”

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

“…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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