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  1. 1

    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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    An enhanced soft set data reduction using decision partition order technique by Mohammed, Mohammed Adam Taheir

    Published 2017
    “…The results show that the decision partition order technique performs up to 50% in parameter reduction, while some algorithms could not obtain any reduction. …”
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    A decision support system for improving forecast using genetic algorithm and tabu search by Ismail, Zuhaimy

    Published 2008
    “…The search for the best parameter value of ?, ? and ? and their combinations using trial and error method is time consuming. …”
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    An Alternative Algorithm for Soft Set Parameter Selection using Special Order by Mohammed, Mohammed Adam Taheir, Wan Maseri, Wan Mohd, Ruzaini, Abdullah Arshah, Mungad, M., Sutoyo, Edi, Chiroma, Haruna

    Published 2015
    “…Also, the proposed algorithm can be used as an effective alternative method for reducing parameters in order to enhance the decision making process. …”
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    A Hybrid Gini PSO-SVM Feature Selection: An Empirical Study of Population Sizes on Different Classifier by Noormadinah Allias, Megat NorulAzmi Megat Mohamed Noor, Mohd. Nazri Ismail, Kim de Silva, (UniKL MIIT)

    Published 2014
    “…Deriving from previous experiments, we extended our work by investigating the effect of population sizes from our proposed method of feature selection on different learning classifier algorithms using Random Forest, Voting, Decision Tree, Support Vector Machine and Stacking. …”
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm by Ramadhanti,, Darin, Larasati, Aisyah, Muid, Abdul, Mohamad, Effendi

    Published 2023
    “…Preventive efforts are needed by predicting the value of churn in the future. This study uses data mining techniques with decision tree algorithms to predict customer churn in one of Indonesian Telecommunication companies. …”
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    Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

    Published 2018
    “…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
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    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    Published 2014
    “…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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    A survey of vertical handover decision algorithms in fourth generation heterogeneous wireless networks by Mahmood, Adnan, Hushairi, Zen, Al-Khalid, Othman

    Published 2013
    “…To offer a systematic comparison, our survey categorized the algorithms in four groups based on the main handover decision criteria used. …”
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    Fuzzy Logic Based Self-Adaptive Handover Algorithm for MobileWiMAX. by Mohd Ali, Borhanuddin, Ismail, Alyani, Noordin, Nor Kamariah, Ben-Mubarak, Mohammed A., Ng , Ben Chee Kyun

    Published 2013
    “…The conventional handover decision algorithm in mobile WiMAX is based on a single criterion, which usually uses the received signal strength indicator (RSSI) as an indicator, with the other fixed handover parameters such as handover threshold and handover margin. …”
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    Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm by Nasruddin, Sholahudin, Satrio P., Mahlia T.M.I., Giannetti N., Saito K.

    Published 2023
    “…Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi-objective genetic algorithm; Objective functions; Passive solar design; Radiant cooling; HVAC; air conditioning; artificial neural network; building; cooling; energy use; genetic algorithm; optimization; temperature effect…”
    Article
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    A review on soft set-based parameter reduction and decision making by Danjuma, Sani, Herawan, Tutut, Ismail, Maizatul Akmar, Chiroma, Haruna, Abubakar, Adamu, Zeki, Akram M.

    Published 2017
    “…The soft set theory as a mathematical tool that deals with uncertainty, imprecise, and vagueness is often employed in solving decision making problem. It has been widely used to identify irrelevant parameters and make reduction set of parameters for decision making in order to bring out the optimal choices. …”
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