Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

“…Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. …”

Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization by Abrar, Shafayat

“…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …”
Get full text
Get full text

SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data by Tekli, Joe

“…While Information Retrieval (IR) systems have gained success in Web-style search engines in the past two decades, nonetheless, the DataBase (DB) paradigm remains prevalent in handling data in enterprise environments and digital libraries, and is gaining even more importance in the Semantic Web with the increasing need to handle partly structured (NoSQL) data. …”
Get full text
Get full text
Get full text
Get full text

Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers by Mansour, N.

“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
Get full text
Get full text
Get full text
Get full text

Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
Get full text
Get full text
Get full text

Adaptive Time-Varying Brain Source Localization by Al-Momani, Sajedah A.

Get full text

حوكمة الذكاء الاصطناعي ضمن أحكام القانون الدولي لحقوق الإنسان by Hilal, Ghofran M. I.

Get full text

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

Get full text

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

Get full text

Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

“…To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …”
Get full text
Get full text
Get full text

The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…This research used High-Resolution Orbitrap-based Mass Spectrometers (HRMS) data to create automated prediction models for the first time in literature. …”

A collaborative filtering recommendation framework utilizing social networks by Aamir Fareed (17019087)

PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY by Noras, J.M.

“…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Energy Research Laboratory (ERL). …”
Get full text

Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

“…This article presents an approach for optimizing load management and scheduling in CubeSat applications to ensure optimal coordination between the load demand, power generation, and energy storage while maintaining communication's quality of service requirements, namely the data rate and bit error rate (BER). The loads are divided into four types based on their priority. …”

Evaluation of C-arm CT metal artifact reduction algorithm during intra-aneurysmal coil embolization by Chintalapani, Gouthami

“…This analysis was carried out to assess the improvements in both brain parenchyma and device visibility with MAR algorithm. Further, ground truth reference images from phantom experiments and clinical data were used for accurate assessment. …”
Get full text
Get full text
Get full text
Get full text

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…”

Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

“…It was found that when solving the Mean-CVaR model with evolutionary algorithms, the risk decreased. The efficient boundary of the PSO algorithm was higher than that of the ICA algorithm, and it displayed more efficient portfolios.Therefore, this algorithm was more successful in optimizing the portfolio.…”