Search Results - (( java implementation path algorithm ) OR ( features selection sensor algorithm ))
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…The performance of our work also been compared with several state-of-the-art of features for selection algorithms.…”
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Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm
Published 2012“…Then, the modified LEACH algorithm was proposed where the improvement was done in cluster head selection based on LEACH. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks
Published 2018“…One of the main features of WSNs is the limited energy of their wireless sensor nodes. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review
Published 2022“…This technique is challenged by the nature of IoT technology and perceived data, as well as by human differences, which necessitated additional processing tasks to select significant features for the learning algorithms. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]
Published 2025“…In this paper, three algorithms were developed: the first was for outlier removal from features, the second was for feature selection, and the third was for partial-features-availability-aware ML model selection. …”
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. This algorithm increased the productivity of OBIA, expedited the process of attribute selection, and resulted in an easy-to-use representation of a knowledge model from a decision tree structure.…”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Feature points selection for markerless hand pose estimation
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…Feature selection is less °exible than feature extrac- tion in that feature selection is, in fact, a special case of feature extraction (with a coe±cient of one for each selected feature and a coe±cient of zero for any of the other features). …”
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Activity recognition using one-versus-all strategy with relief-f and self-adaptive algorithm
Published 2018“…In this paper, we proposed One-versus-All (OVA) strategy with relief-f and self-adaptive algorithm to recognize these activities. Relief-f used to rank the features and prune insignificant features, self-adaptive algorithm selects the relevant ones, and OVA transform features into a series of two-class classification problems, and later recognized by based classifier. …”
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Ensemble Filter Based Feature Selection Technique for Classification of Human Activity Recognition
Published 2025“…Therefore, this research aims to propose a feature selection technique for optimal human activities recognition. …”
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