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31 results for “statistical optimization”
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Research ArticleOpen accessPhrase in the titleStatistical Optimization of Fermentation Conditions for Cellulase Production from Palm Oil Mill EffluentJamal I. Daoud, Md. Zahangir AlamProblem statement: Palm oil mill effluent discharged by the oil palm industries is considered as the mixed of high polluted effluent which is abundant (about 20 million tonnes year-1) and its effect contributes to the serious environmental problems through the pollution of water bodies. Approach: The aim of this study was to identify the potential of low cost substrate such … …American Journal of Environmental Sciences, Vol. 6, Issue 1 · 28 Feb 2010 · 8,192 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThermodynamics, Non-Linear Isotherms, Statistical Modeling and Optimization of Phosphorus Adsorption from WastewaterAkinpelu Kamoru BabayemiPalm Kernel Shell (PKN), an eco-friendly biomass, was carbonized and activated for the removal of phosphorus from wastewater through batch adsorption process. The studies evaluate the effects of pH, particle size, dosage and contact time on the adsorption capacity of the prepared adsorbent. The equilibrium concentration data and the amount of adsorption were described using non-linear regression analysis of the … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 4 · 19 Nov 2016 · 7,512 accessesView PDFCite
Research ArticleOpen accessIn the keywordsQ-Optimizer: An AI-Based Optimization Framework for Efficient SDN Routing and QoS EnhancementDeepthi Goteti, Vurrury Krishna ReddyWith their rigid layers, traditional networks do not meet evolving traffic demands. As a result, they tend to face congestion along with un-optimized routing. SDN controls traffic management by introducing a programmable control plane, enabling dynamic and intelligent network management. However, older routing techniques, such as Dijkstra's and Multipath, suffer from low adaptability, leading to a rise in latency and … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,227 accessesView PDFCite
Research ArticleOpen accessIn the abstractCloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird Optimization-Based Optimal Key GenerationSmita Sharma, Sanjay TyagiMaintaining privacy in the cloud is critical, which implies reliable and effective models that are adapted to the difficulties presented by cloud settings. This paper introduces a comprehensive privacy preservation model tailored specifically for cloud environments, comprising five important phases such as data acquisition, normalization, feature extraction, sanitization and restoration. It begins with the meticulous collection of data from diverse … …Journal of Computer Science, Vol. 21, Issue 7 · 20 Aug 2025 · 3,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Clustering using Two-Stage Eagle Strategy Based on Slime Mould AlgorithmRachid Oucheikh, Achraf Touil, Mouhsene FriDataclustering is considered an important component of data mining which aims tosplit a given dataset into disjoint groups having the same similarities. Thedeveloped techniques for clustering have some challenges to cluster entities incomplex search space and most of them aim to maximize the sum of inter-clusterdistances and minimize the sum of intra-cluster distances. This objectivefunction is nonlinear and hard to … …Journal of Computer Science, Vol. 18, Issue 11 · 7 Nov 2022 · 5,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Bias Detection in Tweets Using Bayesian Probabilistic ModelPrasanth G Rao, Harsha Chigurupati, Krish Hashia et al.Content moderation on social media faces persistent challenges from inconsistent evaluation shaped by subjective judgment and subtle semantic variations. This work proposes a Bayesian probabilistic framework for detecting bias in tweets using WordNet-based vocabulary filtering, statistical normalization via z-scores, and threshold optimization. The system is stateless, scalable, and dataset-agnostic, requiring no session-specific information. Unlike complex models such as Support Vector … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputational Analysis of Genre Effects on Movie Ratings Using MLP AlgorithmsSubir Gupta, Upasana Adhikari, Shefali Varshney, Tanupriya ChoudhuryPredictive analytics are what the entertainment industry depends on so much in prognosticating movie ratings, which is why they inform filmmakers, distributors and stream platforms strategic moves. Traditional prediction models most times only succeed in missing out on the intricate dynamics that are genre-specific to movie ratings thereby leading to inaccuracies and suboptimal decision making. The paper proposes this research … …Journal of Computer Science, Vol. 21, Issue 4 · 19 Mar 2025 · 5,534 accessesView PDFCite
Research ArticleOpen accessIn the abstractBuilding Energy Modeling Using Artificial Neural NetworksMaya Arida, Nabil Nassif, Rand Talib, Taher Abu-LebdehAccurate modeling of total building energy is now vital to reduce energy consumption. This is especially true for buildings since they are considered as the largest energy consumer in the United States. This paper investigates modeling methods for building energy-systems using non-linear auto-regression artificial neural networks. The proposed model can forecast the whole building energy consumptions given the four input … …Energy Research Journal, Vol. 7, Issue 2 · 6 Jun 2017 · 7,125 accessesView PDFCite