Search Results - (( variable negative efficient 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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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…Classifier algorithms, namely the Support Vector Machine and K-Nearest Neighbours were used for benchmarking the performance of the Real-Valued Negative Selection Algorithms. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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FPGA implementation of variable precision Euclid’s GCD algorithm by Al-Haija, Qasem Abu, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Alfarran, Islam

“…Introduction: Euclid's algorithm is well-known for its efficiency and simple iterative to compute the greatest common divisor (GCD) of two non-negative integers. …”
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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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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…These descriptors are characterized by being variable within the urban fabric, resulting in a difference in the shading efficiency in the pedestrian zones. …”
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Statistical analysis engine capacity, weight, and torque on MPV fuel consumption using regression and correlation algorithms by Hafidz Salafuddin, Nanang K. Pradipta, Farrah Anis Fazliatul Adnan, Jong Soo Rhee, Dianta Ginting

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Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission by Ahmad Suki, Che Mohamed Arif

“…SVBR faces several problems, such as the occurrence of unwanted sharp decrease in data rate, buffer overflow, the existence of a low data rate, and the generation of a cyclical negative fluctuation. The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

“…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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Haar cascade algorithm for microsleep detection by Awang, Norkhushaini, Azhar, Ahmad Mirza

“…A finding from the evaluation, however, was a sensitivity to environmental factors as the distance between the driver and the camera increased, the system's accuracy in detecting drowsiness, yawning, and microsleep declined, leading to an increased risk of false negatives. Based on these results, future research should focus on enhancing the core algorithm to be more resilient to variable lighting and distance, thereby reducing false positives and negatives. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

“…Through accumulating positive and negative images of a single object, this algorithm can build a complete classifier capable of classifying different smiles in a limited amount of time (near real time) and with a high level of precision (92.2–98.8%) as opposed to other algorithms by large margins (5% compared with traditional neural network and 2% compared with Deep Neural Network based methods).…”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…We propose a new and efficient approximation of the concentration parameter estimates using two approaches, namely, the roots of a polynomial function and minimizing the negative value of the loglikelihood function in this study. …”
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Data-driven hybrid approaches for renewable power prediction toward grid decarbonization: Applications, issues and suggestions by Hossain Lipu M.S., Miah M.S., Ansari S., Hannan M.A., Hasan K., Sarker M.R., Mahmud M.S., Hussain A., Mansor M.

A new integrated approach for evaluating sustainable development in the electric vehicle sector by Lu, Wen Min, Chou, Chienheng, Ting, Irene Wei Kiong, Liu, Shangming

“…Third, this study uses the classification & regression tree (CART), random forest, and eXtreme gradient boosting (XGBoost) algorithms to assist managers in identifying the key predictive variables for further classification and prediction. …”
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