<![CDATA[Ethereum, as a leading blockchain platform, experiences high variability in transaction fees due to network congestion, gas bidding, and computational complexity. This study analyzes 10,000 Ethereum transactions to identify key factors influencing transaction fees, block density, and staking mechanisms. The results show that transaction fees vary significantly, with an average of 0.1826 ETH and a standard deviation of 0.2381 ETH, indicating substantial fluctuations. A strong positive correlation (r = 0.72) between transaction size and transaction fee confirms that larger transactions incur higher costs due to increased computational demand. Time-series analysis reveals periodic spikes in gas fees, aligning with network congestion patterns. Block density averages 1718.8% (std = 501.01%), showing that some blocks are highly congested while others are underutilized. An Isolation Forest anomaly detection model identifies 3.4% of transactions as outliers, exhibiting unusually high gas fees, which may be caused by priority-based bidding, inefficient smart contract execution, or potential fee manipulation. Further analysis demonstrates that Coin Age and Stake Reward significantly influence transaction success rates. Transactions with older coins show a 7.8% higher success rate, indicating that validators may prioritize transactions with greater historical weight. Additionally, Stake Reward positively affects the Block Generation Rate (p < 0.05), confirming its role in securing the network and optimizing transaction processing. These findings provide valuable insights for Ethereum users, developers, and validators to optimize gas fees, transaction timing, and staking incentives. While this study offers critical observations, future research should focus on real-time gas fee monitoring, deep learning-based congestion forecasting, and the impact of Layer-2 scaling solutions. Understanding Ethereum’s Proof-of-Stake (PoS) dynamics will be essential for ensuring fair transaction processing, reducing gas fees, and improving blockchain efficiency.]]>
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