Social Spider Optimization Algorithm with Gradient Boosting Tree Model for Decision Making in Telemarketing Sector

Abd Al-Aziz Hosni; Sundus Naji; S.S.ASKAR

doi:https://doi.org/10.54216/AJBOR.070101

International Journal of Wireless and Ad Hoc Communication | 2021

Evaluating the Performance of Battery Electric Vehicles using an Incorporated Decision Support Framework Based on Ranking Algorithms

The use of alternative energy sources rather than fossil fuels will be unavoidable in the nearish term due to rising levels of toxic residues that threaten natural life and human health. Furthermore, the use of fossil fuels puts subsequent generations in danger from environmental damage and climate change. Battery electric vehicles (BEVs), an environmentally friendly kind of vehicle, are important in light of transportation's significant contribution to the carbon footprint. In light of the recent fast growth of the BEV industry, it has become more important to consider all available BEV options from the perspective of the end-user. Each BEV's fundamental characteristics may be examined in order to make this evaluation. For the correct BEV buying choice, MCDM strategies are useful. As a result, eleven battery-electric vehicles (BEVs) are considered in this study. A variety of multi-criteria methodologies are used to rate these cars on the basis of their technical specifications, such as acceleration, pricing, battery life, and range. It is then used entropy weight and TOPSIS approaches to gather findings from different MCDM strategies. The entropy method is used to compute the weights of the criteria. Then the TOPSIS is used to rank the options.  The 3 key considerations for BEV choosing are "price," "permitted load," and "energy usage," with Tesla Model S emphasized as the preferred route. 

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Lobna Osman mail

link https://doi.org/10.54216/IJWAC.030203

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

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Journal of Neutrosophic and Fuzzy Systems | 2022

Neutrosophic Crisp minimal Structure

 In this paper, the neutrosophic crisp minimal structure which is a more general structure than the neutrosophic minimal structure is built on neutrosophic crisp sets. The necessary arguments which are neutrosophic minimal crisp open set, neutrosophic minimal crisp closed set, neutrosophic crisp minimal closure, and neutrosophic crisp minimal interior are defined and their basic properties are presented. Also, the neutrosophic crisp minimal structure subspace of neutrosophic crisp minimal structure is defined and studied some of its properties. Finally, many examples are presented. 

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Riad K. Al-Hamido mail

link https://doi.org/10.54216/JNFS.030103

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2022

An Intelligent Bankruptcy Prediction Model based on an Enhanced Sparrow Search Algorithm

Bankruptcy detection becomes one of the major subjects in finance. Indeed, for apparent reasons, several actors like shareholders or managers show more attention to the possibility of a firm’s bankruptcy. Subsequently, various researches are being conducted on the matter of bankruptcy prediction. Recently numerous research works have explored the application of machine learning (ML) techniques to bankruptcy prediction by having financial ratios as predictors. This article devises an Enhanced Sparrow Search Optimization with Deep Learning Enabled Bankruptcy Prediction (ESSODL-BP) model. The proposed ESSODL-BP technique involves the forecasting of the bankruptcy of a financial firm. To accomplish this, the ESSODL-BP technique primarily follows the Z-score normalization approach. Followed by, the bidirectional long short-term memory (BLSTM) model is designed to predict the bankruptcy status of a financial firm. Then, the ESSO algorithm is utilized for optimally tuning the hyperparameters related to the BLSTM model and also boosts the prediction performance to a maximum extent. The performance validation of the ESSODL-BP technique is tested using a benchmark dataset. The experimental outcomes reported better performance of the ESSODL-BP technique over other approaches.

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Abdulaziz Shehab mail -

Mahmood Mahmood mail

link https://doi.org/10.54216/JISIoT.060101

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2022

Development of Sustainable assessment Model of solar hydrogen production techniques: An integrated MCDM approach

Energy has a critical role in human survival and societal progress. Hydrogen is a possible energy carrier for long-term power generation. Known as both an environmental nuisance and an essential hydrogen source, Hydrogen Sulfide (H2S) may be found in large quantities in the waters of the Black Sea. The primary goal of this research is to determine which breakdown processes, such as thermal, thermochemical, electrochemical, plasma, photochemical and thermal suit sustainability requirements better than others. The most acceptable hydrogen generation technique is chosen based on characteristics such as financial viability, environmental viability, effectiveness, simplicity of the process, energy consumption, safety and dependability, application and operational adaptability, and technological maturity. This paper proposes innovative additions to the CoCoSo approach. The COCOSO method is used to compute the weights of criteria and rank the alternatives. This paper proposed 8 criteria and 5 alternatives.

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Mahmoud Ismail mail -

Shereen Zaki mail -

Mahmoud Ibrahim mail

link https://doi.org/10.54216/JISIoT.060102

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

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Fusion: Practice and Applications | 2021

An Effective multicriteria decision-making model for extraction of lithium from seawater/brine: Design and practice

PROMETHEE II decision-making methodologies are integrated into a novel framework in this research. A real-world case study of lithium extraction techniques served as the basis for this investigation. Lithium extraction from brines and saltwater has become more difficult due to the limited natural resources of lithium and the worldwide desire to replace fossil fuels with clean and recyclable energy. Using a multicriteria decision-making approach, the suggested framework aids in selecting the best lithium extraction procedure from brines and saltwater. A case study of lithium extraction from brines and saltwater has been used. The findings of the study show that the suggested strategy is logical and enforceable.

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Mahmoud Ismail mail

link https://doi.org/10.54216/FPA.040104

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2022

Multi-criteria Decision Making Model for Industrial Arc Welding Robot

Industrial robots have made it possible for manufacturers to make elevated low-cost products, which are thus major elements of advanced production technologies. Welding, cleaning, assembling, dismantling, slotting for computer chips, labeling requirements, stacking pallets, quality inspection, and monitoring are just a few of the applications for robotic systems. All the features are completed with a high level of endurance, speed, and accuracy. Multiple and competing criteria must be assessed simultaneously in a comprehensive selection analysis to identify the effectiveness of robots. To provide an automated machine for such arc machining operation, simple multi-criteria decision-making (MCDM) technique based on the COPRAS method is described in this work. The COPRAS method calculates significance weights using objective preferences and ranks the options. The COPRAS technique was used to determine the ranking order. The findings revealed that MCDM techniques for robot selection are extremely useful. The study's peculiarity is that it uses COPRAS MCDM approaches to select industrial arc welding robots.

groups

Lobna Osman mail

link https://doi.org/10.54216/IJWAC.040102

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2021

Experimental study of an automotive air conditioning system with alternative refrigerants

Optimizing efficiency studies were carried out to comply with environmental norms by using MCDM techniques to pick low GWP refrigerants for automotive air conditioning. Multi-criteria optimization for time consumption based on ratio analysis plus full multiplicative form (MULTIMOORA), is being employed in this work to compare 10 distinct alternatives with 10 criteria. Thermal conductivity, vapor pressure, saturation fluid density, latent specific heat, fluid viscosity, GWP, ozone-depleting potential, and cost per pound are among the many response qualities suited for data acquisition in terms of thermodynamics, and environmental stewardship, and economics. It is possible to standardize decision-makers grading and weighting systems using MCDM methodologies. RAA3 had the greatest rank among the 10 refrigerants tested in the MULTIMOORA methodology. The EDAS and TOPSIS techniques identified R-744 to be the worst refrigerant, whereas the MOORA approach showed RAA5 to be the worst refrigerant.

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Mahmoud Ismail mail -

Abduallah Gamal mail

link https://doi.org/10.54216/FPA.050104

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2022

A Novel Glowworm Swarm Optimization Driven Gated Recurrent Unit Enabled Botnet Detection in IIoT Environment

Accurate and prompt detection of security attacks in the Industrial Internet of Things (IIoT) is important to reduce security risks. Since a massive number of IoT devices are placed over the globe and the quantity gets increased, an effective security solution is necessary. A botnet is a computer network comprising numerous hosts executing on standalone software. In this view, this article develops a novel Glowworm Swarm Optimization Driven Gated Recurrent Unit Enabled Botnet Detection (GSOGRU-BD) model in IIoT Environment. The presented GSOGRU-BD model intends to effectually identify the presence of botnet attacks in the IIoT environment. To do so, the GSOGRU-BD model initially pre-processed the input data to get rid of missing values. In addition, the GSOGRU-BD model involves the GRU model for the effective recognition and classification of botnets. Besides, the GSO algorithm is used for optimal hyperparameter tuning of the GRU model. Comparative experimental validation of the GSOGRU-BD model is tested using a benchmark dataset and the results reported the better outcomes for the GSOGRU-BD model. 

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Tarek Gaber mail -

Joseph Bamidele Awotunde mail -

Chin-Shiuh Shieh mail

link https://doi.org/10.54216/JISIoT.060103

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

Details open_in_new

Journal of Neutrosophic and Fuzzy Systems | 2022

Properties of Group Neutro-Topological Space

Unlike traditional algebraic structures, where all operations are well-defined and all axioms are completely true, NeutroAlgebras and AntiAlgebras allow operations to be partially well-defined and axioms to be partially true or fully outer-defined, and axioms to be completely false. These NeutroAlgebras and AntiAlgebras represent a new research subject based on real-world examples. Since an empty set is not a subgroup of a group by observing this, the article leads to learning group neutro-topological space. We introduced the notion of a group neutro-topological space and investigated its properties.

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Bhimraj Basumatary mail -

Binod Chandra Tripathy mail

link https://doi.org/10.54216/JNFS.030104

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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American Journal of Business and Operations Research | 2022

Social Spider Optimization Algorithm with Gradient Boosting Tree Model for Decision Making in Telemarketing Sector

Telemarketing becomes a major tool in enhancing the services of different business sectors. On banking industry, telemarketing is applied to sell products or services. Banking advertisements as well as marketing are majorly based on the detailed information of neutral data related to marketing market and original needs of user for the banks. Decision making becomes an essential part in the telemarketing field that computes a particular class of automated fact in assisting the companies for making decision. Artificial intelligence (AI) is applied for decision making in the telemarketing sector. In this aspect, this paper introduces a social spider optimization (SSOA) with gradient boosting tree (GBT) model for decision making in the telemarketing sector. The main aim of the SSOA-GBT method is to make proper decisions in the telemarketing sectors. To accomplish this, the SSOA-GBT model initially exploits the GBT model for data classification purposes. Next, for improving the performance of the GBT classifier, the SSOA is applied. The performance validation of the SSOA-GBT model is performed using benchmark dataset and the outcomes are investigated in several aspects. The simulation outcomes indicated the better outcomes of the SSOA-GBT approach over the recent approaches. 

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Abd Al-Aziz Hosni El-Bagoury mail -

Sundus Naji AL-Aziz mail -

S.S.ASKAR mail

link https://doi.org/10.54216/AJBOR.070101

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

Details open_in_new