Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

Ma, Tinghuai; Zhou, Hong‐Hao; Jia, Dongdong; Al-Dhelaan, Abdullah; Al-Dhelaan, Mohammed; Tian, Yuan

doi:10.32604/cmes.2019.07758

Cited by 4 publications

(2 citation statements)

References 34 publications

(45 reference statements)

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“…The meeting node defines different reference probabilities for different data packet priorities. If the reference probability of the meeting node is greater than the forwarding probability of the sending node, the data packet is forwarded; otherwise, it is not forwarded [22][23][24]. But these strategies do not adapt to the dynamic changes of the network.…”

Section: Routing Based On Different Businessmentioning

confidence: 99%

A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

Liu

Zhao

et al. 2020

Wireless Communications and Mobile Computing

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With the development of the energy Internet, power communication services are heterogeneous, and different power communication services have different business priorities. The power communication services with different priorities have different requirements for network bandwidth and real-time performance. For traditional unified service, a scheduling method cannot meet these service requirements at the same time, and electric power communication network cannot guarantee the quality of service. Therefore, how to make full use of the time-varying characteristics of communication resources to meet the business needs of different priorities and achieve the goals of high resource utilization and transmission quality has become one of the urgent problems in the power communication network. For this reason, in order to adapt to the real-time congestion of the network, we have designed a packet scheduling method based on the dynamic adjustment of service priority, which dynamically adjusts the priority of the power service on the node; in addition, an evaluation method for the trust value of wireless forwarding nodes is introduced to improve the security of data transmission; and finally, we valuate the channel quality to establish a reasonable and efficient packet scheduling mechanism for services of different priorities. Simulation results show that this method improves the communication performance of high-priority services and improves the spectrum resource utilization of the entire system.

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Section: Routing Based On Different Businessmentioning

confidence: 99%

A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

Liu

Zhao

et al. 2020

Wireless Communications and Mobile Computing

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show abstract

“…For machine learning experts who must handle complicated data, FS is essential. It is frequently used in machine learning, data mining, and pattern recognition [3][4][5]. FS methods have previously been seen in video classification, image retrieval, gender classification, vehicle identification, and other applications [6,7].…”

Section: Introductionmentioning

confidence: 99%

BHGSO: Binary Hunger Games Search Optimization Algorithm for Feature Selection Problem

Devi¹,

Premkumar²,

Jangir³

et al. 2022

Computers, Materials &Amp; Continua

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In machine learning and data mining, feature selection (FS) is a traditional and complicated optimization problem. Since the run time increases exponentially, FS is treated as an NP-hard problem. The researcher's effort to build a new FS solution was inspired by the ongoing need for an efficient FS framework and the success rates of swarming outcomes in different optimization scenarios. This paper presents two binary variants of a Hunger Games Search Optimization (HGSO) algorithm based on V-and S-shaped transfer functions within a wrapper FS model for choosing the best features from a large dataset. The proposed technique transforms the continuous HGSO into a binary variant using V-and S-shaped transfer functions (BHGSO-V and BHGSO-S). To validate the accuracy, 16 famous UCI datasets are considered and compared with different state-of-the-art metaheuristic binary algorithms. The findings demonstrate that BHGSO-V achieves better performance in terms of the selected number of features, classification accuracy, run time, and fitness values than other state-of-the-art algorithms. The results demonstrate that the BHGSO-V algorithm can reduce dimensionality and choose the most helpful features for classification problems. The proposed BHGSO-V achieves 95% average classification accuracy for most of the datasets, and run time is less than 5 sec. for low and medium dimensional datasets and less than 10 sec for high dimensional datasets.

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An improved PIO feature selection algorithm for IoT network intrusion detection system based on ensemble learning

Alghanam

Almobaideen

Saadeh

et al. 2023

Expert Systems with Applications

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Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

Cited by 4 publications

References 34 publications

A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

BHGSO: Binary Hunger Games Search Optimization Algorithm for Feature Selection Problem

An improved PIO feature selection algorithm for IoT network intrusion detection system based on ensemble learning

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