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Segmentation of brain MR images with directional weighted optimized fuzzy C-means clustering by Arshad, Javed, Wang, Yin Chai, Narayanan, Kaluthramaiyer

“…FCM algorithm is not robust against noise. In this paper, we proposed an enhanced version of Fuzzy C-Means algorithm that incorporates spatial information into the membership function for clustering of brain MR images. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Surveillance camera placement optimization using Particle Swarm Optimization (PSO) algorithm and Mixed-Integer Linear Programming (MILP) model / `Ain Safia Roslan by Roslan, `Ain Safia

“…The study applied these optimization techniques to various Binary Integer Programming (BIP) matrix sizes (11×9, 39×24, and 172×49) representing the same 2D layouts, to evaluate their performance in different spatial configurations. …”
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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications by Far Chen, Jong

“…The second layer employed spatial data and the fuzzy Technique for Order Preference by Similarity to Ideal Solution algorithm to refine potential solar energy sites, yielding the top 100 optimal locations. …”
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Workload performance evaluation of large spatial database for DSS based disaster management by Rohman, Muhammad Syaifur

“…The Case Based Reasoning (CBR) optimized with Hash Search Technique has been adopted in this study for the purpose of evaluating and predicting the workload performance of PostgreSQL DBMS. …”
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Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

“…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The improvement process involved segmentation, feature selection and classification techniques. A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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Optimization of substation grounding grid design for horizontal and vertical multilayer and uniform soil condition using Simulated Annealing method by Permal N., Osman M., Ariffin A.M., Boopalan N., Abidin Ab Kadir M.Z.

Holographic mode-selective launch for bandwidth enhancement in multimode fiber by Amphawan, Angela

“…With rapidly growing bandwidth demands in Local Area Networks, it is imperative to support next generation speeds beyond 40Gbit/s.Various holographic optimization techniques using spatial light modulators have recently been explored for adaptive channel impulse response improvement of MMF links. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…The GA-based approach is used to optimize the various features obtained. It encodes the temporal and spatial filter estimates and optimize the feature selection with respect to the classification error. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…This algorithm maintains the local optimal radius of micro-clusters rather than a global and constant radius. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Enhancement of Single and Composite Images Based on Contourlet Transform Approach by Melkamu, Hunegnaw Asmare

“…Image enhancement is an imperative step in almost every image processing algorithms. Numerous image enhancement algorithms have been developed for gray scale images despite their absence in many applications lately. …”
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Existence and uniqueness for the evolutionary impulse control problem using an asynchronous algorithms by Haiour M., Bencheikh Le Hocine M.E.A., Jan R., Himadan A., Boulaaras S.

“…Our approach unfolds through a four-step methodology, leveraging distinctive features of a discrete iterative technique. This methodology integrates semi-implicit techniques with respect to the variable t and employs spatial approximation via finite element methods. …”

Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia by Kim Hwang Y., Zamri Ibrahim M., Ismail M., Najah Ahmed A., Albani A.

Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking by Ong, Chor Keat

“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

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On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee by Wong , Soo Mee

“…However, existing approaches and techniques for spatial characterisation are highly reliant on the presence and manual identification of a well-separated characteristics target. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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Instant Sign Language Recognition by WAR Strategy Algorithm Based Tuned Machine Learning by Abd Al-Latief S.T., Yussof S., Ahmad A., Khadim S.M., Abdulhasan R.A.

“…Afterward, the WAR Strategy optimization algorithm has been adopted in two procedures, first in optimizing the extracted set of features, and second to fine-tune the hyperparameters of six standard machine learning models in order to achieve precise and efficient sign language recognition. …”