Search Results - (( variable waste control algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…In addition, several algorithms were implemented to measure the other important image variables such as froth velocity,froth color and bubble collapse rate. …”
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Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm by Hannan M.A., Akhtar M., Begum R.A., Basri H., Hussain A., Scavino E.

Fault detection and diagnosis for gas density monitoring using multivariate statistical process control by Norul Shahida, Che Din, Noor Asma Fazli, Abdul Samad, Chin, Sim Yee

“…Multivariate analysis technique i.e., Principal Component Analysis (PCA) and Partial Correlation analysis (PCorrA) are used to determine the correlation coefficients between the process variables and quality variables while control chart with the calculated correlation coefficients are used to facilitate the Fault Detection and Diagnosis (FDD) algorithm. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Hybrid HCS-fuzzy mppt algorithm for hydrokinetic energy harnessing by Wan Ismail, Ibrahim, Mohd Rusllim, Mohamed, Raja Mohd Taufika, Raja Ismail

“…The proposed algorithm is the combination of the Fuzzy Logic Controller (FLC) and HCS algorithm to provide the variable step-size to eradicate the limitation of conventional HCS algorithm. …”
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IMPLEMENTATION OF ADVANCED PROCESS CONTROL FOR FLOW CONTROL APPLICATION by ROSLI, NURFATIHAH SYALWIAH

“…The most difficult process variable (PV) to control is flow due to the property changes in fluid and fast response. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…By employing these methods, organizations can effectively allocate resources and exercise control over costs. Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Operator Training Simulator Using Plantwide Control for Biodiesel Production from Waste Cooking Oil by Shikchand Patle, Dipesh

“…Later, the performance of the developed control system is assessed in terms of settling time, deviation from the production target (DPT), and overall total variation (TV) in manipulated variables. …”
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Microgrid multi-distributed energy resources for power management network stability / Bilal Mouneir Saeed Eid by Bilal Mouneir, Saeed Eid

“…A model for the Photovoltaic (PV) array and three-phase grid-connected inverter shows the control parameters. The inverter’s controller uses inner and outer control loops to control the injected current and DC voltage. …”
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Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

“…The model training flow will have 2 classifier groupings which are control group and auto machine learning (ML) where feature selection with redundancy elimination method to be applied on input data to reduce the number of variables to minimum prior modeling flow. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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