Search Results - (( data distribution path algorithm ) OR ( _ pollution ((tree algorithm) OR (model algorithm)) ))

Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

“…Decision trees; Eutrophication; Forecasting; Learning systems; Neural networks; Phosphate fertilizers; Predictive analytics; Reservoirs (water); Stochastic systems; Support vector machines; Water pollution; Water quality; Water supply; Conventional modeling; Cross validation; Developed model; Non-point source pollution; Prediction model; Primary sources; Statistical indices; Water quality parameters; Learning algorithms…”

Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

“…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). A large number of attributes were discovered with the C4.5 DM algorithm, which also generated the classification model as a decision tree. …”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

“…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”

An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…The paper will primarily observe, visualize and anticipate pollution levels. In particular, three algorithms of Artificial Intelligence were used to create good forecasting models and a predictive AQI model for 4 distinct gases: carbon dioxide, sulphur dioxide, nitrogen dioxide, and atmospheric particulate matter. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

“…The paper will primarily observe, visualize and anticipate pollution levels. In particular, three algorithms of Artificial Intelligence were used to create good forecasting models and a predictive AQI model for 4 distinct gases: carbon dioxide, sulphur dioxide, nitrogen dioxide, and atmospheric particulate matter. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…The random forest outperformed other algorithms with a very high R2 of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…The random forest outperformed other algorithms with a very high R2 of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

“…Accordingly, the development of air quality predictive models can be very useful as such models can provide early warnings of pollution levels increasing to unsatisfactory levels. …”

A Continuous Overlay Path Probing Algorithm For Overlay Networks by Feily, Maryam

“…Several experiments were carried out using the OMNeT++ simulation framework. The designed algorithm was evaluated using experimental data. The obtained results show that the continuous in-band overlay path probing algorithm (COPPA) provides up-to-date bandwidth information with reduced overhead and minimal impact on the traffic of the path.…”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

Classification prediction of PM10 concentration using a tree-based machine learning approach by Wan Nur Shaziayani, Ul-Saufie, Ahmad Zia, Mutalib, Sofianita, Mohamad Noor, Norazian, Zainordin, Nazatul Syadia

“…Therefore, in this study, three machine learning algorithms—namely, decision tree (DT), boosted regression tree (BRT), and random forest (RF)—were applied for the prediction of PM10 in Kota Bharu, Kelantan. …”
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Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

“…In this paper, we have analysed the performance of the ZigBeePRO network by applying the shortest path algorithm while delivering energy data from the solar DRG to the SG. …”
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Evaluation of machine learning in predicting air quality index / Abdullah Sani Abdul Rahman, Aizal Yusrina Idris and Suhaimi Abdul Rahman by Abdul Rahman, Abdullah Sani, Idris, Aizal Yusrina, Abdul Rahman, Suhaimi

“…Three machine learning algorithms, namely Generalized Linear Model, Decision Tree and Support Vector Machine are used in this research. …”
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Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks by Moghanjoughi, Ayyoub Akbari

“…Ants’ algorithm belongs to the Swarm Intelligence (SI), which is proposed to find the shortest path. …”
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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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Traffic management algorithms for LEO satellite networks by Huyop @ Ayop, Fahrul Hakim

“…In dealing with traffic routing problem, two algorithms, Dijkstra's Shortest Path and Genetic Algorithm (GA) are combined together and enhanced to re-strategize a better routing mechanism for a heterogeneous mix of traffic classes ranging from traditional voice calls to multimedia data services in Low Earth Orbit (LEO) satellite networks. …”
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Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

“…This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). …”
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Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN by Ibrahim, Nurul Saliha Amani

“…Due to finite resource, multiple issues need to be considered in designing such system, including AG flight time, coverage radius and the achievable data rate of the ground-to-air system, thus an Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. …”
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Synchronization algorithm for remote heterogeneous database environment by Imam, A.A., Basri, S.B., Ahmad, R.B.

“…In this paper, we proposed a model and a unique algorithm to synchronize data between heterogeneous databases, in order to provide alternative synchronization paths, concurrency in operation and bidirectional mode of data exchange. …”
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