Search Results - (( waste selection method algorithm ) OR ( variable detection mining algorithm ))

Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

“…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”

Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud M.A., Ahmad M.S., Ahmad A., Mustapha A., Yusoff M.Z.M., Hamid N.H.A.

“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”

Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

“…Many studies have been conducted in order to predict cancer. Different data mining method has showed up with its related algorithms were adopted by different research. …”
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud, Moamin Ahmed, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mustapha, Aida, Mohd Yusoff, Mohd Zaliman, Abdul Hamid, Nurzeatul Hamimah

“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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Development and implementation of a technique for norms-adaptable agents in open multi-agent communities by Mahmoud M., Ahmad M.S., Mohd Yusoff M.Z.

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…”

Sentiment-analysis to detect early depressive symptom in Bangla language from social media: a review study by Hassan, Md. Hasibul, Kamaruddin, Azrina, Azmi Murad, Masrah Azrifah

“…The review shows that the mostly used method in Sentiment-analysis is Machine Learning in the field of Opinion-mining. Furthermore, we have identified another variable that can be included to improve the existing algorithm.…”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Toward Predicting Student�s Academic Performance Using Artificial Neural Networks (ANNs) by Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Alsariera Y.A., Ali A.Q., Hashim W., Tiong S.K.

“…No pattern was detected regarding selecting the input variables as they are mainly based on the context of the study and the availability of data. …”

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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Optimization of process parameters for pyrolsis of waste plastics by T method-1 by Shankaran A/l Thiyagarajan

Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

“…The model output optimisation by genetic algorithm (GA) produces higher biogas production compared to the optimisation using statistical methods. …”
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Incorporation of High Recyclability Material Selection in Computer Aided Design by Zahari, Taha, Sakundarini, Novita, Salwa Hanim, Abdul-Rashid, Raja Ariffin, Raja Ghazilla

“…In this paper, the use of fuzzy inference system and genetic algorithm is proposed to optimize the multi-objective problem in the selection of recyclable materials. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…Infected palms are asymptomatic throughout the disease's early stages, making disease detection challenging. The survival of affected trees must detect BSR at the mild infected (T1) stage. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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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

“…Primarily, this research is about the optimization of triaxial ceramic employing the POFA process by the Taguchi design and Flower Pollination Algorithm (FPA). The recycled POFA was evaluated through the POFA layer formation method where selected POFA layers were employed as filler raw material. …”
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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

“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
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