Search Results - (( developing effective prediction algorithm ) OR ( java simulation optimization algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
Get full text
Get full text

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
Get full text
Get full text
Get full text

Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text

OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
Get full text
Get full text

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
Get full text
Get full text

Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
Get full text
Get full text
Get full text
Get full text

Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
Get full text
Get full text

Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
Get full text
Get full text

Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
Get full text
Get full text

Algorithm for the legal regulation of internet financial crime by Ambaras Khan, Hanna, Ab. Rahman, Suhaimi, Xinxin, Mao

“…The experimental results indicated that the random forest algorithm demonstrated effective prediction abilities, with actual crime rates closely matching the predicted rates in both test and experimental samples. …”
Get full text
Get full text
Get full text

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. Another objective of the study is to develop and compare the prediction models for electrical energy demand of one day-ahead. …”
Get full text
Get full text

Development of hybrid artificial intelligent based handover decision algorithm by Aibinu, Abiodun Musa, Onumanyi, Adeiza J., Adedigba, A. P., Ipinyomi, M., Folorunso, T. A., Salami, Momoh Jimoh Eyiomika

“…Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. …”
Get full text
Get full text
Get full text
Get full text

Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…Then the developed prediction tool was tested in the Muscat coordinates. …”
Get full text
Get full text

Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023 by Soomro, Anam, Zakariyah, Habeebullah, Aftab, S.M.A., Muflehi, Mohamad, Shah, Asadullah, Meraj, Syeda

“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. …”
Get full text
Get full text
Get full text
Get full text
Get full text

A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

“…This study focuses on comparing the performance of three machine learning algorithms, namely Naive Bayes (NB), Support Vector Machines (SVM), and Random Forest (RF), in predicting diabetes using two datasets: Pima Indians Diabetes Dataset (PIDD) and the Diabetes 2019 Dataset (DD2019), and the need to identify the most accurate and effective algorithm for diabetes prediction. …”
Get full text
Get full text
Get full text

Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…Additionally, we tested how scale-optimisation responded to species' size, taxonomic associations (species and genus), study area and algorithm. We found that choice of algorithm had strong effect in determining the differences between SDMs' spatial predictions, while bootstrapping had no effect. …”
Get full text
Get full text

REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
Get full text
Get full text

Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail by Ismail, Muhammad Sirajuddin

“…This study aims to investigate the requirements of utilizing the Artificial Neural Network algorithm for prediction of dengue outbreak. The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. …”
Get full text
Get full text

Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani by Jailani, Muhammad Irfan Zahin

“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
Get full text
Get full text