Papers by Parimal Kumar Giri
Deep Machine Learning
Advances in data mining and database management book series, Apr 19, 2024
Fog Computing Approaches for Sustainable Smart Cities
International journal of reasoning-based intelligent systems, 2024
Predicting and Diagnosing Self-Intermittent Faults in A Dynamic Distributed Attack on Wireless Sensor Network
International Journal of Business Continuity and Risk Management, Dec 31, 2023
The Privacy-Preserving High-Dimensional Synthetic Data Generation and Evaluation in the Healthcare Domain
Advances in data mining and database management book series, Apr 19, 2024
Recognizing the Best Set of Key Actors for Collaborative Performance from Large Social Networks1
Social Science Research Network, 2022
A Meta Heuristic Optimization based Deep Learning Model for Fake News Detection in Online Social Networks
International Journal of Electronic Security and Digital Forensics
Link Recommendation for Social Influence Maximization
Smart Innovation, Systems and Technologies, 2022
Performance of Machine Learning Techniques Before and After COVID-19 on Indian Foreign Exchange Rate
Smart Innovation, Systems and Technologies, 2022
Malaysian Journal of Computer Science
Many people use online social networks to share their opinions and information in this digital ag... more Many people use online social networks to share their opinions and information in this digital age. The number of people engaged and their dynamic nature pose a major challenge for social network analysis (SNA). Community detection is one of the most critical and fascinating issues in social network analysis. Researchers frequently employ node features and topological structures to recognize important and meaningful performance in order to locate non-overlapping communities. We introduce a locally and globally tuned multi-objective biogeography-based optimization (LGMBBO) technique in this research for detecting overlapping communities based on the number of connections and node similarity. Four real- world online social network datasets were used in the experiment to assess the quality of both overlapping and non-overlapping partitions. As a result, the model generates a set of solutions that have the best topological structure of a network with node properties. The suggested model...
A Meta Heuristic Optimization based Deep Learning Model for Fake News Detection in Online Social Networks
International Journal of Electronic Security and Digital Forensics
Machine learning approaches to sentiment analysis in online social networks
International Journal of Work Innovation
Power of Network Stochasticity
Locally and Globally Tuned Chaotic Biogeography-Based Optimization Algorithm
2017 International Conference on Information Technology (ICIT), 2017
In this paper, we have used chaotic maps to improve locally and globally tuned biogeography-based... more In this paper, we have used chaotic maps to improve locally and globally tuned biogeography-based optimization (LGBBO) algorithm. The effect of chaotic maps like Chebyshev, Logistic, Sinusoidal, and Circle for enhancing the efficiency of LGBBO are studied in terms of local optima avoidance and convergence speed, and we name it as Locally and Globally Tuned Chaotic BBO(LGCBBO). We have carried out an extensive numerical evaluation on ten high dimensional benchmark functions to measure the efficiency of our proposed method. The experimental study confirms that LGCBBO is better than LGBBO for some chaotic maps in terms of accuracy and convergence rate.
A Survey on Soft Computing Techniques for Multi-Constrained QoS Routing in MANET
—Mobile Ad-hoc Networks (MANETs) is a collection of mobile nodes that dynamically create a wirele... more —Mobile Ad-hoc Networks (MANETs) is a collection of mobile nodes that dynamically create a wireless network amongst them without using any infrastructure. Due to resource constraints and dynamic topology, supporting Quality of Service (QoS) in MANETs is a challenging task. The problem of QoS routing is difficult and to find a feasible route multi-constraints is NP-Complete problem. Neural Networks (NNs) and Evolutionary algorithms promise solutions to such complicated problems, they have been used successfully in various practical applications. In order to provide a comprehensive understanding of the solutions designed for MANETs and their related issues and to pave way for further research, a survey of QoS concept on the basis of disparate routing schemes, intelligence field including Neural Networks and Evolutionary Algorithm concepts has been discussed.
Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks
Credit risk assessment is acting as a survival weapon in almost every financial institution. It i... more Credit risk assessment is acting as a survival weapon in almost every financial institution. It involves an in-depth and sensitive analysis of various economic, social, demographic, and other pertinent data provided by the customers and about the customers for building a more accurate and robust electronic finance system. The classification problem is one of the primary concerns in the process of analyzing the gamut of data; however, its complexity has ignited us to use machine learning-based approaches. In this paper, radial basis function neural network (RBFNN) with particle swarm optimization (RBFNN + PSO) and improved particle swarm optimization tuned radial basis function neural network (RBFNN + IMPSO) learning algorithms have been studied and compared their effectiveness for credit risk assessment. The experimental findings draw a clear line between the proposed model and traditional learning algorithms. Moreover, the proposed method is very promising vis-a-vis of individual c...
Intelligent Systems in Accounting, Finance and Management, 2021
Dampak atas pergerakan bebas barang dan jasa, akhir-akhir ini sering terjadi kasus-kasus Impor Pa... more Dampak atas pergerakan bebas barang dan jasa, akhir-akhir ini sering terjadi kasus-kasus Impor Paralel, impor paralel terjadi ketika seorang importer memasukan barang-barang asli (Genuine Products) dan secara paralel kemudian bersama-sama dengan penerima lisensi yang sah menjual barang tersebut dengan harga yang lebih murah daripada barang yang sama (grenuine products) yang dijual oleh penerima lisensi yang sah yang dari pemilik hak kekayaan intelektual. Permasalahan dalam artikel ini adalah praktik impor paralel dalam sistem Hukum Indonesia. Penelitian ini bertujuan untuk mengetahui, memahai dan menganalisis praktik impor paralel dalam sistem Hukum Indonesia. Metode yang digunakan adalah penelitian hukum normatif, menggunakan pendekatan perundang-undangan yang terkait dengan Impor Paralel dalam sistem Hukum Indonesia. Hasil dari penelitian jurnal ini adalah Indonesia menetapkan doktrin national exhaustion berdasarkan frasa "Pemegang Paten memiliki hak eksklusif untuk melaksanakan paten yang dimilikinya dan untuk melarang pihak lain yang tanpa persetujuannya mengimpor produk paten miliknya yang telah didaftarkan di Indonesia dari pasar luar negeri untuk dijual kembali di Indonesia.
Journal of King Saud University - Computer and Information Sciences, 2018
Biogeography Based Optimization (BBO) is a population based metaheuristic algorithm using the ide... more Biogeography Based Optimization (BBO) is a population based metaheuristic algorithm using the idea of migration and mutation operation of species for solving complex optimization problems. BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. It has also been applied to real world optimization problems of type linear or nonlinear, nominal or ordinal as well as mixed variables. But, it is realized that adaptation of the intensification and diversification for solving complex optimization problems are challenging tasks. To cope with these challenges, we develop a novel migration model for BBO which inherits features of the nearest neighbour of the local best individual to be migrated along with a global best individual of the pool. Furthermore to select the local best individual for the habitat to be migrated an adaptive local topological structure has been used. We name it as ''Adaptive Neighbourhood for Locally and Globally Tuned Biogeography Based Optimization algorithm (ANLGBBO)". This maintains the balance between intensification and diversification i.e., improve solution by exploiting the accumulated search space and exploring the large space by identifying regions with high quality solutions. We have carried out an extensive numerical evaluation and comparisons for experimental tests using twenty benchmark functions with different features to measure the efficiency of the algorithm. The experimental study confirms ANLGBBO draws clear line of other variants of BBO algorithms in terms of population diversity and establish the accuracy of global optimal solution.
A Simulink Implementation of the Cerebellum Model Articulation Controller
2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies, 2010
Lecturer, Electrical Asst. Prof., IT Asst. Prof., ICE ... Apeejay College of Engg. Apeejay Colleg... more Lecturer, Electrical Asst. Prof., IT Asst. Prof., ICE ... Apeejay College of Engg. Apeejay College of Engg Apeejay College of Engg ... Abstract This paper presents a Simulink implementation of the CMAC controller which was proposed by JSAlbus. The controller was implemented ...
Biogeography-Based Optimization (BBO) is a nature-inspired meta-heuristic algorithm, which uses t... more Biogeography-Based Optimization (BBO) is a nature-inspired meta-heuristic algorithm, which uses the idea of the migration strategy of animals or other species for solving complex optimization problems. In BBO, adaptation of the intensification and diversification for solving complex optimization problem is a challenging task. Migration and mutation operators are two imperative features that largely affect the performance and computational efficiency in BBO, which maintains both exploration and exploitation of existing approaches. In this paper, an innovative migration operator has been introduced in BBO, which inherit the features from a nearest neighbor of the local best individual to be migrated to the globally best individual of the pool and we name it as “Locally and Globally Tuned BBO (LGBBO)”. We have carried out an extensive numerical evaluation on ten benchmark functions to measure the efficiency of the proposed method. The experimental study confirms that LGBBO is better th...
This Software for Design Activity in power plants Equipments helps the power plant engineers and ... more This Software for Design Activity in power plants Equipments helps the power plant engineers and managers to manage the development and design activities of equipments in the field of power plants. This paper is basically concerned with the computerization of the design activity of Condenser, vital equipment in Heat Exchanger Unit (HEU) of Thermal power plant required for condensing the steam and for further reclaimable purposes to achieve economy. This software will also provide facilities to maintain user profile and the respective work details. The study use a developed model which estimates software effort by studying and analyzing small and medium scale application software.
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Papers by Parimal Kumar Giri