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Bidirectional LSTM-Based Energy Consumption Forecasting:Advancing AI-Driven Cloud Integration for Cognitive City Energy Management

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Computers, Materials & Continua 2025年第5期83卷 2907-2926页

作者： Sheik Mohideen Shah Meganathan Selvamani Mahesh Thyluru Ramakrishna Surbhi Bhatia Khan Shakila Basheer Wajdan Al Malwi Mohammad Tabrez Quasim Department of Computer Science and Engineering Srinivasa Ramanujan CentreSASTRA Deemed UniversityKumbakonam612001India Department of Computer Science and Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bangalore562112India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia Centre for Research Impact and Outcome Chitkara University Institute of Engineering and TechnologyChitkara UniversityRajpura140401PunjabIndia Department of Information Systems College ofComputer and Information SciencePrincessNourah bintAbdulrahmanUniversityP.O.Box 84428Riyadh11671Saudi Arabia College of Computer Science Informatics and Computer Systems Department King Khalid UniversityAbha61421Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Efficient energy management is a cornerstone of advancing cognitive cities,where AI,IoT,and cloud computing seamlessly integrate to meet escalating global energy *** this context,the ability to forecast electricity consumption with precision is vital,particularly in residential settings where usage patterns are highly variable and *** study presents an innovative approach to energy consumption forecasting using a bidirectional Long Short-Term Memory(LSTM)*** a dataset containing over twomillionmultivariate,time-series observations collected froma single household over nearly four years,ourmodel addresses the limitations of traditional time-series forecasting methods,which often struggle with temporal dependencies and non-linear *** bidirectional LSTM architecture processes data in both forward and backward directions,capturing past and future contexts at each time step,whereas existing unidirectional LSTMs consider only a single temporal *** design,combined with dropout regularization,leads to a 20.6%reduction in RMSE and an 18.8%improvement in MAE over conventional unidirectional LSTMs,demonstrating a substantial enhancement in prediction accuracy and *** to existing models—including SVM,Random Forest,MLP,ANN,and CNN—the proposed model achieves the lowest MAE of 0.0831 and RMSE of 0.2213 during testing,significantly outperforming these *** results highlight the model’s superior ability to navigate the complexities of energy usage patterns,reinforcing its potential application in AI-driven IoT and cloud-enabled energy management systems for cognitive *** integrating advanced machine learning techniqueswith IoT and cloud infrastructure,this research contributes to the development of intelligent,sustainable urban environments.

关键词： Deep learning bidirectional LSTM energy consumption forecasting time-series analysis predictive modeling machine learning in energy management

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Runtime thread rescheduling: An extended scheduling algorithm to enhance the performance of the Gridbus Broker

Runtime thread rescheduling: An extended scheduling algorith...

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11th International Conference on Computer and Information Technology, ICCIT 2008

作者： Hussain, Altaf Shoeb, Abu Awal Md. Bikas, Md. Abu Naser Hasan, Mohammad Khalad Department ofComputer Science and Engineering Shahjalal University of Science and Technology Sylhet Bangladesh

ISBN: (纸本)9781424421367

Grid computing is becoming a requirement for the processing of large amount of data now-a-days. The Gridbus broker schedules jobs depending on data and compute resources. Current scheduling process does not reassign a job from lower compute resource to higher compute resource higher compute resource is available. In this paper' we have proposed a technique to reassign a thread to higher grade executor by preempting the thread in lower grade executor by using the data restoration technique which track the information of the thread so far ran on a lower rate compute resource. It is done only there is an idle higher computer resource is available. The peiformance as well as the reliability ofthe Grid has been improved by this approach in a considerable extent.

关键词： Grid computing

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A decision tree based quasi-identifier perturbation technique for preserving privacy in data mining

A decision tree based quasi-identifier perturbation techniqu...

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2009 3rd International Conference on Research Challenges in Information science, RCIS 2009

作者： Dai, Bi-Ru Lin, Yang-Tze Department ofComputer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781424428656

Classification is an important issue in data mining, and decision tree is one of the most popular techniques for classification analysis. Some data sources contain private personal information that people are unwilling to reveal. The disclosure of person-specific data is possible to endanger thousands of people, and therefore the dataset should be protected before it is released for mining. However, techniques to hide private information usually modify the original dataset without considering influences on the prediction accuracy of a classification model. In this paper, we propose an algorithm to protect personal privacy for classification model based on decision tree. Our goal is to hide all person-specific information with minimized data perturbation. Furthermore, the prediction capability of the decision tree classifier can be maintained. As demonstrated in the experiments, the proposed algorithm can successfully hide private information with fewer disturbances of the classifier. © 2009 IEEE.

关键词： Decision trees

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Assessing and improving authentication confidence management

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Information Management and Computer Security 2010年第2期18卷 124-139页

作者： Pearce, Michael Zeadally, Sherali Hunt, Ray Department of Computer Science and Software Engineering University of Canterbury Christchurch New Zealand Department of Computer Science and Information Technology University of the District of Columbia Washington DC United States Department OfComputer Science and Software Engineering University of Canterbury Christchurch New Zealand

Purpose-The purpose of this paper is to address some weaknesses in the handling of current multi-factor authentication, suggests some criteria for overcoming these weaknesses and presents a simple proof of concept authentication system. Design/methodology/approach-First, this paper evaluates some of the underlying practices and assumptions in multi-factor authentication systems. Next, the paper assesses the implications of these when compared to a quantitative authentication risk management approach. Based upon these implications this paper next note the requirements for an improved system and detail some related research areas that meet these requirements. Finally, this paper discussed how a system that meets these requirements through the application of that research could provide benefits and outlined a simple points-based authentication system. Findings-The paper proposes that many of the weaknesses in authentication confidence management could be effectively mitigated through the deployment of a factor independent multi-modal fusion quantitative authentication-based system. This paper details a simple point-based approach that does this and discuss how addressing the problems in handling authentication confidence could further optimise risk management in multi-factor authentication systems. Practical implications-This paper's suggestions for optimising multi-factor authentication have many implications within medium to high-security commercial and government applications. Correct authentication risk handling enables decisions regarding risk and authentication to be made more accurately. Originality/value-This implications of the issues discussed in this paper have relevance to anyone who deploys or uses any medium to high-security authentication system. As the bottom end of the medium to high-security range includes online banking, there are implications for a wide range of stakeholders. © Emerald Group Publishing Limited.

关键词： Authentication

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Converged PKI-based authorization, authentication management and delegation for an e-business

Converged PKI-based authorization, authentication management...

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2008 1st International Conference on Distributed Frameworks and Application, DFmA 2008

作者： Mani Anand, K.P. Narayanasam, P. Department ofComputer Science and Engineering College of Engineering Anna University Chennai-600 025 Tamil Nadu India

ISBN: (纸本)9781424423132

Real E-business System has some vulnerable facts like denial of service;unavailability of distributed certificates and also creates inconsistency policy by independent stakeholders these leads to enhance the domain by converging PKI-based security services. The proposed system makes use of an existing e-business infrastructure and adds security services such as access control, authentication management and delegation by integrating AC-based DAC, X.509 PMI and X509 ID Certificates respectively. The mechanism was evidently integrated into an existing ebusiness infrastructure with the use of network security packages that are available in PKI to make the e-business applications more robust. © 2008 IEEE.

关键词： Authentication

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Faster convex optimization: Simulated annealing with an efficient universal barrier 33

Faster convex optimization: Simulated annealing with an effi...

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33rd International Conference on Machine Learning, ICML 2016

作者： Abernethy, Jacob Hazan, Elad Department ofComputer Science and Engineering University of Michigan United States Department of Computer Scicnce Princeton University United States

ISBN: (纸本)9781510829008

This paper explores a surprising equivalence between two seemingly-distinct convex optimization methods. We show that simulated annealing, a well-studied random walk algorithms, is directly equivalent, in a certain sense, to the central path interior point algorithm for the the en- tropic universal barrier function. This connection exhibits several benefits. First, we are able improve the state of the art time complexity for convex optimization under the membership oracle model by devising a new temperature schedule for simulated annealing motivated by central path following interior point methods. Second, we get an efficient randomized interior point method with an efficiently computable universal barrier for any convex set described by a membership oracle. Previously, efficiently computable barriers were known only for particular convex sets. © 2016 by the author(s).

关键词： Simulated annealing

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A scenario-based model to improve the quality of software inspection process

A scenario-based model to improve the quality of software in...

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4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012

作者： Taba, Navid Hashemi Ow, Siew Hock Department of Software Engineering Faculty OfComputer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781467331135

Independent researches of expert groups and scientific papers show that , although some testing models and automated and manual tools are mostly used, but still some software and software projects deal with important defects that may lead to project failure. Most of software inspection models are independent of software developing process and concentrating on inspection artifacts. In this article, the proposed model is based on software developing phases adapted predefined scenarios. This inspection approach removes some possible defects in each of software development phase and avoids amplifying these defects in each of the next phases. Defect learning is the interesting point of scenario-based proposed model. Learning is a basic factor for a model to be intelligent. In this model a learning plan is created and executed through which, according to founded results, inspection process is modified and updated. The efficiency of model is evaluated through a case study. © 2012 IEEE.

关键词： Software testing

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Effective Prediction of Autism Disease using Data Mining Techniques 6

Effective Prediction of Autism Disease using Data Mining Tec...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Aishwarya, D. Charulatha, R.P. Niranjan, M. Malathi, K. Department ofComputer Science and Engineering Karpagam Academy of Higher Education Coimbatore India Department of Computer Science and Engineering Karpagam Academy of Higher Education Coimbatore India

ISBN: (纸本)9798350398496

The medical costs associated with autism spectrum disorder (ASD), a neurodevelopmental condition, can be significantly reduced with early identification. However, lengthy wait times and high costs come along with an ASD diagnosis. The cost of autism and the increase in ASD cases globally highlight the urgent need for the development of straightforward screening methods. A short and useful ASD test will soon be available to help healthcare professionals and allow people determine whether a formal clinical diagnosis is required or not. ASD cases are rising globally, necessitating the need for datasets pertaining to behavioral features. Due to the dearth of such datasets, it is difficult to perform in-depth research to improve the efficiency, sensitivity, specificity, and predictive accuracy of the ASD screening technique. There are currently only few diagnostic or screening trials, and the greater part of databases on autism are genetic in origin. A brand-new dataset with twenty characteristics is proposed for adult autism screening. Upcoming study may benefit from this information, particularly when identifying the fundamental components of autism and improving the classification of individuals with ASD. The ten behavioural variables (AQ-10Adult) and ten personality traits includedin this dataset can be used to identify ASD cases from controls, according to behavioural study. © 2023 IEEE.

关键词： Diagnosis

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Cardiovascular Disease Prediction with Convolutional Neural Networks and Hyperparameter Tuning 8th

Cardiovascular Disease Prediction with Convolutional Neural ...

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8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Hossain, Mohammad Alamgir Metwally, Abdelnasser Abdelwakil Khan, Asif Ali Amin, Sherif Tawfik Hamdan, Alfadil Ahmed Limkar, Suresh Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department ofComputer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department ofComputer and Network Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department of Artificial Intelligence & Data Science AISSMS Institute of Information Technology Maharashtra Pune India

ISBN: (纸本)9789819765805

CVD continues to pose a substantial global health burden, demanding the need for the creation of precise predictive models that can aid in the timely identification and evaluation of risks. This research paper aims to provide a thorough examination of the prediction of CVD by utilizing CNN in aggregation with hyperparameter tuning techniques. This paper examines the effectiveness of three widely recognized CNN architectures, namely ResNet, VGGNet, and Xception CVD. The Tree-structured Parzen Estimator (TPE) is utilized as a method for tuning hyperparameters in order to optimize the CNN models. The study commences with a comprehensive examination of the dataset, encompassing a wide array of cardiovascular CT image data. The chosen CNN architectures serve as the fundamental framework for our predictive models. The selection of these architectures is based on their established track record in effectively addressing image analysis tasks and their capacity to accurately capture complex patterns and features present in medical images. The models undergo training using a dataset in order to acquire knowledge about distinctive features that are linked to various cardiovascular conditions. The experimental findings presented in the study indicate that the utilization of the Xception architecture, in aggregation with TPE for hyperparameter optimization, yields the most favorable predictive accuracy. Specifically, the achieved accuracy rate of 98.26% is notably remarkable. This result highlights the significance of not only choosing advanced CNN architectures but also optimizing their hyperparameters to fully exploit their potential in predicting cardiovascular disease. This establishes it as a promising tool for the early diagnosis and risk assessment of CVD. This study establishes a fundamental basis for future investigations in the advancement of precise and dependable predictive models applicable to various medical imaging contexts. © The Author(s), under exclusive license

关键词： Diseases

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Exact analysis of some split-merge queues 33

Exact analysis of some split-merge queues

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33rd International Symposium on Computer Performance, Modeling, Measurement, and Evaluation, IFIP WG 7.3 Performance 2015

作者： Fiorini, Pierre M. Lipsky, Lester CF Search Marketing PortsmouthNH03801 United States Department ofComputer Science and Engineering University of Connecticut United States

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