BIG DATA PROCESSING AND CORRELATION ANALYSIS OF ELECTRIC POWER MARKETING BASED ON IMPROVED APRIORI ALGORITHM AND RDD MODEL
To solve the problems of traditional Apriori algorithm in power marketing big data processing, such as candidate item set redundancy, low single-machine computing efficiency, and difficulty in adapting to multi-dimensional time series data, this study proposes an improved Apriori algorithm that integrates Resilient Distributed Dataset (RDD) distrib...
By Fan Pan, Lingen Zhou, Lu Gan, Wei Kang, Xiaolei Li
AN INFLUENCER NODE IDENTIFICATION USING HYBRID MACHINE LEARNING TECHNIQUES
Influential node detection in networks is vital in diverse applications, particularly with the online social networks (OSNs). Measures of centrality, traditional ones, fail to sufficiently describe the influence of nodes on complex and multilayered networks. This paper presents a novel hybrid method that combines traditional topological centrality ...
By CS. Saradha
LEVERAGING STRATEGIC MARKETING ANALYTICS TO DRIVE COMPETITIVE ADVANTAGE IN DATA-DRIVEN MARKETS
This research paper examines how the strategic marketing analytics, which combines big data, artificial intelligence (AI), and knowledge management can be used to improve the competitive advantage in data-driven markets. The research tests the effectiveness of AI-driven analytics in enhancing the performance of the market, customer high retention a...
By M. Venith Vijay, Vijayakanthan Selvaraj, R. Muzhumathi, P. Sundara BalaMurugan
PROXIMAL CARIES DETECTION USING YOLOV11 IN NEAR-INFRARED LIGHT TRANSILLUMINATION IMAGES
The study will be conducted to complement the diagnosis of proximal caries lesions that are difficult to improve due to their location between the teeth, as shown in Near-Infrared Light Transillumination (NILT) photographs. It was proposed to enhance caries detection with a semantic segmentation model based on YOLOv11, which is more specific in det...
By Asma Alatawi, Wdaee Alhalabi, Hani Nassar, Arwa Basbrain, Hattan Jamalellail, Mohammed Alsadat
MULTI-OBJECTIVE TOPOLOGY OPTIMIZATION OF 3D PRINTED LATTICE STRUCTURES FOR LIGHTWEIGHT AUTOMOTIVE COMPONENTS
The automotive industry is increasingly focused on developing lightweight, fuel-efficient, and structurally robust components to meet stringent performance and sustainability requirements. Additively manufactured lattice structures have emerged as a promising solution due to their high strength-to-weight ratio, energy absorption capability, and geo...
By Sapna Bawankar, Priya Vij
BIOGENIC SYNTHESIS AND ANTIBACTERIAL ACTIVITY OF SILVER NANOPARTICLES USING CYANOBACTERIA FROM THE ARID REGION OF HAIL, SAUDI ARABIA
This research paper examines the biogenic production of silver nanoparticles (AgNPs) using cyanobacterial strains (Spirulina, Nostoc, and Anabaena) that have been isolated in arid areas, Hail, in Saudi Arabia, and determines their antimicrobial effects in relation to multi-drug-resistant pathogens. Synthesis was done by incubating cyanobacterial bi...
By Sana M. Alenezi, Amal A. Al-Hazzani, Fatimah S. Alkhattaf
ANALYZING THE STABILITY OF SMART GRIDS USING POLICY-BASED REINFORCEMENT LEARNING MODEL
The stability of smart grids (SG) plays a critical role in improving the stability of power supply, particularly when system failures or sensor breakdowns could occur and result in a lack of input data. This paper provides a new method of prediction of smart grid consistency by using a Gradient Policy prediction model, which is based on reinforceme...
By S. Mahendran, B. Gomathy
A TWO – ECHELON INVENTORY MODEL FOR DETERIORATING ITEMS WITH RAMP – TYPE DEMANDS AND VARIABLE HOLDING COSTS
It presents a dynamic model of inventory management of the deteriorating items with time-sensitive demand and variable holding costs. The model is used to solve the problem in industries where demand is seasonal or because of other external conditions, like weather or market conditions. A two-tier inventory model is implemented as a way of minimizi...
By Prashant Sharma, Birendra Kumar Chauhan, Gajraj Singh
DEEP REINFORCEMENT LEARNING CONTROL OF SWARM UAVS FOR POST DISASTER CIVIL INFRASTRUCTURE ASSESSMENT
Rapid and accurate assessment of civic infrastructure following a natural or artificial disaster is essential to planning emergency response and recovery. This paper introduces a control system based on deep reinforcement learning (DRL) to coordinate unmanned aerial vehicle (UAV) swarms and methodically approach the post-disaster infrastructure ins...
By Moti Ranjan Tandi, Archana Mishra
ENHANCING MACHINE LEARNING CLASSIFIERS WITH GLOBALBESTPSO FOR CLASSIFYING BANK CUSTOMERS
The innovation of Machine Learning (ML) techniques is evolving from basic techniques to optimized techniques, considerably improving the performance of prediction models. In the proposed work, the study primarily explores fundamental ML classification methods to classify banking customers based on their credit information. The classification of cus...
By Sufaira Shamsudeen, K. Ranjith Singh