Search Results - (( loading classifications means algorithm ) OR ( java application sensor algorithm ))

Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…This method will give the best result when clustering the overlapped data in load profile. PNN is a fast training process to do the classification activities. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

“…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory by Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N.

An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus by Abdalla, E.A.H., Nallagownden, P., Nor, N.B.M., Romlie, M.F., Hassan, S.M.

“…The studied ANFIS-based FCS outperforms the ANFIS-based fuzzy C-means clustering in terms of the regression. Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Subsequently,the filtered signal containing useful information was extracted by three methods  root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks by Nirabi, Ali, Abd Rahman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

“…This study introduces a thoughtfully curated dataset compris- ing electroencephalogram (EEG) recordings designed to un- ravel mental stress patterns through the perspective of cogni- tive load. The dataset incorporates EEG signals obtained from 15 subjects, with a gender distribution of 8 females and 7 males, and a mean age of 21.5 years [ 1 ]. …”
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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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Generating an adaptive and robust walking pattern for prosthetic ankle-foot utilizing a nonlinear autoregressive network with exogenous inputs / Hamza Al Kouzbary by Hamza, Al Kouzbary

“…This three-level control structure has at least one element of discrete transition properties that requires many sensors to improve classification accuracy. However, these sensors also lead to higher computational load and costs. …”
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Feature extraction of power disturbance signal using time frequency analysis by Sihab, Norsabrina

“…As a conclusion, SVD and PCA are useful to apply in TFD to extract important feature vectors then MMC can measure the distance metric between those mean vectors. Furthermore, all the features obtained are useful features and can be used for power disturbance classification and recognition with DSP approach as well as to maintain power quality…”
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Support vector machine for day ahead electricity price forecasting by Razak I.A.B.W.A., Abidin I.B.Z., Siah Y.K., Rahman T.K.B.A., Lada M.Y., Ramani A.N.B., Nasir M.N.M., Ahmad A.B.

“…This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). …”

Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…Attribute selection through Information Gain Attrite Evaluation model highlighted Program Code, Course Code and Type of Course as the strongest predictors of course approval and demand levels. Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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