Search Results - (( developing waste selection algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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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.

“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions by Nur Azriati, Mat

“…This research focuses on two solid waste management (SWM) problems, particularly the landfill site selection problem (LSSP) and the waste collection vehicle routing problem (WCVRP). …”
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Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm by Ting S.C., Ismail A.R., Malek M.A.

Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm by Tan, Chee Kuan

“…In this project, evolutionary prototype methodology was selected to smooth the software development according to the scopes and also the requirements. …”
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Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

“…This problem can be best resolved by promoting end-of-life (EOL) selection strategies. The main objective of this research is to develop an evaluation system for selecting EOL strategy specifically for remanufacturing. …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…Badly designed timetables are not just inconvenient but proved expensive in terms of wasting time and money. Hence, the major aim of this research is to investigate the internal mechanism of genetic algorithm in solving and improving class timetabling problem. …”
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Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

“…Classification of dry waste garbage is crucial since incorrect labelling of dry waste types may contribute huge loss to waste industry. …”
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Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm by Zainudin, Azlan

“…The combustion of wasted palm oil materials leads to the formation of Palm Oil Fuel Ash (POFA). …”
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das by Utpal, Kumar Das

“…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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Genetic Algorithm based Fuzzy Logic Controller for Optimal Charging-Discharging of Energy Storage in Microgrid applications by Faisal M., Hannan M.A., Ker P.J., Muttaqi K.M.

PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK by Sivaraos, Kumaran K., Dharsyanth R., Amran M., Shukor S.M., Pujari S., Ramasamy D., Vatesh U.K., Mahdi Al-Obaidi A.S.H., Ramesh S., Lee K.Y.S.

“…Experimental data consisting of 27 sets of control parameters and corresponding dimensional outputs were used to train and validate the ANN model. The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”