Search Results - (( parametric classification learning algorithm ) OR ( variable optimization path algorithm ))

Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

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The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

“…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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Path optimization using genetic algorithm in laser scanning system by Chen, Chai Phing, Koh, Johnny Siaw Paw, Aris, Ishak, Fong, Albert Yu Chooi, Tiong, Sieh Kiong

“…In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. …”
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Path optimization using genetic algorithm in laser scanning system by Chen C.P., Koh S.P., Aris I.B., Albert F.Y.C., Tiong S.K.

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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

“…Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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Runtime reduction in optimal multi-query sampling-based motion planning by Khaksar W., Sahari K.S.B.M., Ismail F.B., Yousefi M., Ali M.A.

Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

“…This study investigates the application of Decision Trees (DTs), a non-parametric supervised learning method, renowned for its simplicity, interpretability, and wide applicability in various domains, including machine learning for classification and regression tasks. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

“…However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. …”

Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques by Kayalvily, Tabianan, Denis, Arputharaj, Mohd Norshahriel, Abd Rani, Sarasvathi, Nahalingham

“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

“…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. …”
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Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

“…Here, a routing tree is constructed based on the energy/bit minimization routing (EbMR). This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.…”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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Resource Efficient For Hybrid Fiber-Wireless Communications Links In Access Networks With Multi Response Optimization Algorithm by Wong, Adam Yoon Khang, Indra, Win Adiyansyah, Jamil Alsayaydeh, Jamil Abedalrahim, Mohamat Gani, Johar Akbar, M. Idrus, Sevia, Pusppanathan, Jaysuman

“…This work proposes a Multi response Optimization (MO) algorithm, named MO-LMMHOWAN that apply in Last Mile Mobile Hybrid Optical Wireless Access Network (LMMHOWAN). …”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

“…This research presents the optimal switching sequence path to minimize power losses during the network switching operation. …”
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